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Research statement, what is a research statement.

The research statement (or statement of research interests) is a common component of academic job applications. It is a summary of your research accomplishments, current work, and future direction and potential of your work.

The statement can discuss specific issues such as:

• funding history and potential
• requirements for laboratory equipment and space and other resources
• potential research and industrial collaborations
• how your research contributes to your field
• future direction of your research

The research statement should be technical, but should be intelligible to all members of the department, including those outside your subdiscipline. So keep the “big picture” in mind. The strongest research statements present a readable, compelling, and realistic research agenda that fits well with the needs, facilities, and goals of the department.

Research statements can be weakened by:

• overly ambitious proposals
• lack of clear direction
• lack of big-picture focus
• inadequate attention to the needs and facilities of the department or position

Why a Research Statement?

• It conveys to search committees the pieces of your professional identity and charts the course of your scholarly journey.
• It communicates a sense that your research will follow logically from what you have done and that it will be different, important, and innovative.
• It gives a context for your research interests—Why does your research matter? The so what?
• It combines your achievements and current work with the proposal for upcoming research.
• areas of specialty and expertise
• potential to get funding
• academic strengths and abilities
• compatibility with the department or school
• ability to think and communicate like a serious scholar and/or scientist

Formatting of Research Statements

The goal of the research statement is to introduce yourself to a search committee, which will probably contain scientists both in and outside your field, and get them excited about your research. To encourage people to read it:

• make it one or two pages, three at most
• use informative section headings and subheadings
• use bullets
• use an easily readable font size
• make the margins a reasonable size

Organization of Research Statements

Think of the overarching theme guiding your main research subject area. Write an essay that lays out:

• The main theme(s) and why it is important and what specific skills you use to attack the problem.
• A few specific examples of problems you have already solved with success to build credibility and inform people outside your field about what you do.
• A discussion of the future direction of your research. This section should be really exciting to people both in and outside your field. Don’t sell yourself short; if you think your research could lead to answers for big important questions, say so!
• A final paragraph that gives a good overall impression of your research.

Writing Research Statements

• Avoid jargon. Make sure that you describe your research in language that many people outside your specific subject area can understand. Ask people both in and outside your field to read it before you send your application. A search committee won’t get excited about something they can’t understand.
• Write as clearly, concisely, and concretely as you can.
• Keep it at a summary level; give more detail in the job talk.
• Ask others to proofread it. Be sure there are no spelling errors.
• Convince the search committee not only that you are knowledgeable, but that you are the right person to carry out the research.
• Include information that sets you apart (e.g., publication in  Science, Nature,  or a prestigious journal in your field).
• What excites you about your research? Sound fresh.
• Include preliminary results and how to build on results.
• Point out how current faculty may become future partners.
• Acknowledge the work of others.
• Use language that shows you are an independent researcher.
• BUT focus on your research work, not yourself.
• Include potential funding partners and industrial collaborations. Be creative!
• Provide a summary of your research.
• Put in background material to give the context/relevance/significance of your research.
• List major findings, outcomes, and implications.
• Describe both current and planned (future) research.
• Communicate a sense that your research will follow logically from what you have done and that it will be unique, significant, and innovative (and easy to fund).

Describe Your Future Goals or Research Plans

• Major problem(s) you want to focus on in your research.
• The problem’s relevance and significance to the field.
• Your specific goals for the next three to five years, including potential impact and outcomes.
• If you know what a particular agency funds, you can name the agency and briefly outline a proposal.
• Give broad enough goals so that if one area doesn’t get funded, you can pursue other research goals and funding.

Identify Potential Funding Sources

• Almost every institution wants to know whether you’ll be able to get external funding for research.
• Try to provide some possible sources of funding for the research, such as NIH, NSF, foundations, private agencies.
• Mention past funding, if appropriate.

Be Realistic

There is a delicate balance between a realistic research statement where you promise to work on problems you really think you can solve and over-reaching or dabbling in too many subject areas. Select an over-arching theme for your research statement and leave miscellaneous ideas or projects out. Everyone knows that you will work on more than what you mention in this statement.

Consider Also Preparing a Longer Version

• A longer version (five–15 pages) can be brought to your interview. (Check with your advisor to see if this is necessary.)
• You may be asked to describe research plans and budget in detail at the campus interview. Be prepared.
• Include laboratory needs (how much budget you need for equipment, how many grad assistants, etc.) to start up the research.

Samples of Research Statements

To find sample research statements with content specific to your discipline, search on the internet for your discipline + “Research Statement.”

• University of Pennsylvania Sample Research Statement
• Advice on writing a Research Statement (Plan) from the journal  Science

3+ SAMPLE Research Accomplishment Report in PDF

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Writing a Research Statement (with example)

Much like writing a teaching philosophy , a research statement takes time, energy, and a lot of self reflection. This statement is a summary of your research accomplishments, what you are currently working on, and the future direction of your research program. This is also the place to really highlight your potential contributions to your field. For researchers who are further along in their career, this statement may include information about funding applications that were reviewed, approved, as well as any applications that are going to be submitted within the next year.

When I’ve looked at research statements over the years, helping people prepare for the academic interview cycle, one thing I’ve noticed more than anything is that people tend focus solely on the tangible aspects of their research, essentially rehashing their CV or resume. Although their accomplishments are often great, it can result in a rather boring set of pages full of nitty-gritty details rather than an immersive story about research experiences and potential. If there is one thing you take away from this article, your research path is magical and you want your readers to be invested in your magical story .

Now, I realize in my particular area of research (statistics and numerical reasoning), magical is not the word that most people would use as a descriptor. But therein lies the catch. When you are applying for academic positions, you aren’t selling just your research focus. Rather, you are selling the idea of you, your work, and your potential. Yes, your focus is a part of this, but only one part. You are the truly magical component, and your research is just one aspect of that.

When I did my cycle through academic application season, I wanted the review board to see who I was as a researcher, but I also wanted them to see how I approached my research content. The value my research adds to the field is the icing on the cake. I know my research is valuable. Generally speaking, scientists agree that most research in always valuable. But I needed the review board to see more than just my research value because I was competing against literally hundreds of applications. In such a competitive arena, every component of my application portfolio needed to stand out and grab attention.

As with other aspects of your portfolio, your research statement has some core components:

• a brief summary of your research program
• an overarching research question that ties all the individual studies together
• what you are currently working on
• where your research program is expected to go

Talking through these core aspects in a serial, linear way can be rather … Boring. You definitely do not want to be placed in the discard pile simply because your portfolio wasn’t engaging enough.  Which brings me to storytelling.   When I say storytelling, I’m not saying academics need to be master weavers of fantasy, complete with plots and characters that draw people out of reality into an imaginary world. Instead, I mean that people need to be walked through a narrative that logically carries the reader from one sentence to the next. This research statements connects the readers to you and invests them in your future research potential. Every sentence should be designed to make them want to keep reading.

Don’t feel bad if this statement takes some time to draft. Not all of us are naturally gifted with the talent for wordsmithing. It, like many other aspects of your portfolio, takes time, effort, energy, and self-reflection. Each aspect should be built with thoughtfulness and insight, and those things cannot be drawn overnight. Take your time and really develop your ideas. Over time, you’ll find that your research statement will evolve into a mature, guiding light of where you’ve been and where you’re going. And your readers will enjoy placing your files in the accept pile.

Alaina Talboy, PhD Research Statement Example

“Science and everyday life cannot and should not be separated.” – Rosalind Franklin

Research Interests

     Over the last eight years, my research interests have focused on how people understand and utilize information to make judgments and decisions. Of particular interest are the mechanisms which underlie general abilities to reason through complex information when uncertainty is involved.  In these types of situations, the data needed to make a decision are often presented as complicated statistics which are notoriously difficult to understand. In my research, I employ a combination of quantitative and qualitative research methods and analyses to evaluate how people process statistical data, which has strong theoretical contributions for discerning how people may perceive and utilize statistics in reasoning and decision making. This research also has valuable practical implications as statistical reasoning is one of the foundational pillars required for scientific thinking. I plan to continue this research via several avenues in both theoretical and applied contexts.

Statistics and the Reference Class Problem

     It is easy to feel overwhelmed when presented with statistics, especially when the meaning of the statistical data is not clear. For example, what does it mean when the newscaster says there is a 20% chance of showers? Does that mean it will only rain 20% of the day? Or that only 20% of the area will get rain? Or that 20% of the possible rain will actually fall? Without a knowing the appropriate reference class, or group from which the data are drawn, reasoners are often forced to make a decision based on an improper assessment of the numbers provided. (The correct answer is that out of 100 days with these weather conditions, rain occurs on 20 of them.) Although this is a rather benign version of the reference class problem, difficulties with this issue extends well into the very core of understanding statistics.

     Statistical testing involves an inherently nested structure in which values are dependent on the expression of other values. Understanding these relationships are foundational for appropriate use and application of statistics in practice. However, difficulties understanding statistics has been widely documented throughout numerous fields, contributing to the current research crisis as well as patient diagnostic errors (e.g., Gelman & Loken, 2014; Ioannidis, 2005; Ioannidis, Munafò, Fusar-Poli, Nosek, & David, 2014; Pashler & Wagenmakers, 2012). Therefore, research that can improve general statistical literacy is highly sought after. 

     As a stepping stone toward the more difficulty reference classes in statistics, a slightly less complicated version of the reference class problem can be found in Bayesian reasoning tasks (e.g., Gigerenzer, Gaissmaier, Kurz-Milcke, Schwartz, & Woloshin, 2007; Gigerenzer & Hoffrage, 1995; Hoffrage, Krauss, Martignon, & Gigerenzer, 2015; Johnson & Tubau, 2015; Reyna & Brainerd, 2008; Sirota, Kostovičová, & Vallée-Tourangeau, 2015; Talboy & Schneider, 2017, 2018, in press). In these types of reasoning tasks, there are difficulties with representing the inherently nested structure of the problem in a way that clearly elucidates the correct reference class needed to determine the solution. Additionally, computational demands compound these representation difficulties, contributing to generally low levels of accuracy.

     In my own research, we have tackled the representational difficulties of reasoning by fundamentally altering how information is presented and which reference classes are elucidated in the problem structure (Talboy & Schneider, 2017, 2018, in press).  In a related line, we break down the computational difficulties into the component processes of identification, computation, and application of values from the problem to the solution (Talboy & Schneider, in progress). In doing so, we discovered a general bias in which reasoners tend to select values that are presented in the problem text as the answer even when computations are required (Talboy & Schneider, in press, in progress, 2018). Moving forward, I plan to apply the advances made in understanding how people work through the complicated nested structure of Bayesian reasoning tasks to the more difficult nested structure of statistical testing.

Reference Dependence in Reasoning

     While completing earlier work on a brief tutorial designed to increased understanding of these Bayesian reasoning problems through both representation and computation training (Talboy & Schneider, 2017), I realized that the reasoning task could be structurally reformed to focus on the information needed to solve the problem rather than using the traditional format which focuses on conflicting information that only serves to confuse the reasoner. In doing so, we inadvertently found a mechanism for reference dependence in Bayesian reasoning that was not previously documented (Talboy & Schneider, 2018, in press). 

     Reference dependence is the tendency to start cognitive deliberations from a given or indicated point of reference, and is considered to be one of the most ubiquitous findings through judgment and decision making literature (e.g., Dinner, Johnson, Goldstein, & Liu, 2011; Hájek, 2007; Lopes & Oden, 1999; Tversky & Kahneman, 1991). Although the majority of research documenting reference dependence comes from the choice literature, the importance of context in shaping behavior has also been noted in several other domains, including logical reasoning (Johnson-Laird, 2010), problem solving (Kotovsky & Simon, 1990), extensional reasoning (Fox & Levav, 2004)—and now in Bayesian reasoning as well (Talboy & Schneider, 2018, in press).

     I parlayed my previous research on representational and computational difficulties into the foundation for my dissertation, with an eye toward how reference dependence affects uninitiated reasoners’ abilities to overcome these obstacles (Talboy, dissertation). I also evaluated the general value selection bias to determine the circumstances in which uninitiated reasoners revert to selecting values from the problem rather than completing computations (Talboy & Schneider, in progress, in press). I plan to extend this line of research to further evaluate the extent to which a value selection bias is utilized in other types of reasoning tasks involving reference classes, such as relative versus absolute risk.

Advancing Health Literacy

     Although the majority of my research focuses on the theoretical underpinnings of cognitive processes involved in reasoning about inherently nested problem structures, I also have an applied line of research that focuses on applying what we learn from research to everyday life. We recently published a paper geared toward the medical community that takes what we learned about Bayesian reasoning and applies it to understanding the outcomes of medical diagnostic testing, and how patients would use that information to make future medical decisions (Talboy & Schneider, 2018). I also led an interdisciplinary team on a collaborative project to evaluate how younger and older adults evaluate pharmaceutical pamphlet information to determine which treatment to use (Talboy, Aylward, Lende, & Guttmann, 2016; Talboy & Guttmann, in progress). I plan to continue researching how information presented in medical contexts can be more clearly elucidated to improve individual health literacy, as well as general health decision making and reasoning.

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Writing an Effective Research Statement

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A research statement is a summary of research achievements and a proposal for upcoming research. It often includes both current aims and findings, and future goals. Research statements are usually requested as part of a relevant job application process, and often assist in the identification of appropriate applicants. Learn more about how to craft an effective research statement.

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Research statements for faculty job applications

The purpose of a research statement.

The main goal of a research statement is to walk the search committee through the evolution of your research, to highlight your research accomplishments, and to show where your research will be taking you next. To a certain extent, the next steps that you identify within your statement will also need to touch on how your research could benefit the institution to which you are applying. This might be in terms of grant money, faculty collaborations, involving students in your research, or developing new courses. Your CV will usually show a search committee where you have done your research, who your mentors have been, the titles of your various research projects, a list of your papers, and it may provide a very brief summary of what some of this research involves. However, there can be certain points of interest that a CV may not always address in enough detail.

• What got you interested in this research?
• What was the burning question that you set out to answer?
• What challenges did you encounter along the way, and how did you overcome these challenges?
• How can your research be applied?
• Why is your research important within your field?
• What direction will your research take you in next, and what new questions do you have?

While you may not have a good sense of where your research will ultimately lead you, you should have a sense of some of the possible destinations along the way. You want to be able to show a search committee that your research is moving forward and that you are moving forward along with it in terms of developing new skills and knowledge. Ultimately, your research statement should complement your cover letter, CV, and teaching philosophy to illustrate what makes you an ideal candidate for the job. The more clearly you can articulate the path your research has taken, and where it will take you in the future, the more convincing and interesting it will be to read.

Separate research statements are usually requested from researchers in engineering, social, physical, and life sciences, but can also be requested for researchers in the humanities. In many cases, however, the same information that is covered in the research statement is often integrated into the cover letter for many disciplines within the humanities and no separate research statement is requested within the job advertisement. Seek advice from current faculty and new hires about the conventions of your discipline if you are in doubt.

Timeline: Getting Started with Your Research Statement

You can think of a research statement as having three distinct parts. The first part will focus on your past research and can include the reasons you started your research, an explanation as to why the questions you originally asked are important in your field, and a summary some of the work you did to answer some of these early questions.

The middle part of the research statement focuses on your current research. How is this research different from previous work you have done, and what brought you to where you are today? You should still explain the questions you are trying to ask, and it is very important that you focus on some of the findings that you have (and cite some of the publications associated with these findings). In other words, do not talk about your research in abstract terms, make sure that you explain your actual results and findings (even if these may not be entirely complete when you are applying for faculty positions), and mention why these results are significant.

The final part of your research statement should build on the first two parts. Yes, you have asked good questions and used good methods to find some answers, but how will you now use this foundation to take you into your future? Since you are hoping that your future will be at one of the institutions to which you are applying, you should provide some convincing reasons why your future research will be possible at each institution, and why it will be beneficial to that institution and to their students.

While you are focusing on the past, present, and future or your research, and tailoring it to each institution, you should also think about the length of your statement and how detailed or specific you make the descriptions of your research. Think about who will be reading it. Will they all understand the jargon you are using? Are they experts in the subject, or experts in a range of related subjects? Can you go into very specific detail, or do you need to talk about your research in broader terms that make sense to people outside of your research field, focusing on the common ground that might exist? Additionally, you should make sure that your future research plans differ from those of your PI or advisor, as you need to be seen as an independent researcher. Identify 4-5 specific aims that can be divided into short-term and long-term goals. You can give some idea of a 5-year research plan that includes the studies you want to perform, but also mention your long-term plans so that the search committee knows that this is not a finite project.

Another important consideration when writing about your research is realizing that you do not perform research in a vacuum. When doing your research, you may have worked within a team environment at some point or sought out specific collaborations. You may have faced some serious challenges that required some creative problem-solving to overcome. While these aspects are not necessarily as important as your results and your papers or patents, they can help paint a picture of you as a well-rounded researcher who is likely to be successful in the future even if new problems arise, for example.

Follow these general steps to begin developing an effective research statement:

Step 1: Think about how and why you got started with your research. What motivated you to spend so much time on answering the questions you developed? If you can illustrate some of the enthusiasm you have for your subject, the search committee will likely assume that students and other faculty members will see this in you as well. People like to work with passionate and enthusiastic colleagues. Remember to focus on what you found, what questions you answered, and why your findings are significant. The research you completed in the past will have brought you to where you are today; also be sure to show how your research past and research present are connected. Explore some of the techniques and approaches you have successfully used in your research, and describe some of the challenges you overcame. What makes people interested in what you do, and how have you used your research as a tool for teaching or mentoring students? Integrating students into your research may be an important part of your future research at your target institutions. Conclude describing your current research by focusing on your findings, their importance, and what new questions they generate.

Step 2: Think about how you can tailor your research statement for each application. Familiarize yourself with the faculty at each institution, and explore the research that they have been performing. You should think about your future research in terms of the students at the institution. What opportunities can you imagine that would allow students to get involved in what you do to serve as a tool for teaching and training them, and to get them excited about your subject? Do not talk about your desire to work with graduate students if the institution only has undergraduates! You will also need to think about what equipment or resources that you might need to do your future research. Again, mention any resources that specific institutions have that you would be interested in utilizing (e.g., print materials, super electron microscopes, archived artwork). You can also mention what you hope to do with your current and future research in terms of publication (whether in journals or as a book); try to be as specific and honest as possible. Finally, be prepared to talk about how your future research can help bring in grants and other sources of funding, especially if you have a good track record of receiving awards and fellowships. Mention some grants that you know have been awarded to similar research, and state your intention to seek this type of funding.

Step 3: Ask faculty in your department if they are willing to share their own research statements with you. To a certain extent, there will be some subject-specific differences in what is expected from a research statement, and so it is always a good idea to see how others in your field have done it. You should try to draft your own research statement first before you review any statements shared with you. Your goal is to create a unique research statement that clearly highlights your abilities as a researcher.

Step 4: The research statement is typically a few (2-3) pages in length, depending on the number of images, illustrations, or graphs included.  Once you have completed the steps above, schedule an appointment with a career advisor to get feedback on your draft. You should also try to get faculty in your department to review your document if they are willing to do so.

Additional Resources

For further tips, tricks, and strategies for writing a research statement for faculty jobs, see the resources below:

• The PhD Career Training Platform is an eLearning platform with on-demand, self-paced modules that allow PhDs and postdocs to make informed decisions about their career path and learn successful job search strategies from other PhDs. Select the University of Pennsylvania from the drop-down menu, log in using your University ID, and click the “Faculty Careers” tab to learn more about application documents for a faculty job search.
• Writing an Effective Research Statement
• Research Statements for Humanities PhDs
• Tips to Get Started on Your Research Statement (video)

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WTO / Business / Statements / Research Statement Examples: How To Structure + Expert Tips

Research Statement Examples: How To Structure + Expert Tips

When applying for a faculty position, a research statement (or summary of research interests) is a document that outlines an applicant’s experience, including interests, accomplishments, ongoing research, and future goals. The selection committee uses the document to determine if your interests and experience align with the department, institution, or program. 

Research is valuable in academia. Educators and educational institutions contribute to society by researching important social, scientific, or medical issues. It is thus a vital consideration when being selected for any faculty position. Key elements of the statement include; funding history and potential collaborations; project requirements, such as laboratory equipment, facilities, etc., and the proposed direction of upcoming projects. Include a summary of the contributions made by your past and present projects to other fields, your field of study, and the profession (along with an explanation of why this is a good fit).

A strong research statement should be comprehensive, technical enough for academics in the field, but broad enough for selection committee members from other disciplines. 

Some common flaws in the document include unclear direction and vagueness, overly ambitious or unrealistic proposals, a failure to focus on the big picture, and a misalignment with the faculty’s goals, needs, and facilities. Use this article to learn more about how to create a suitable research statement that improves your application for a faculty position.

Research Statement Examples

What a Good Research Statement Must Include  

The statement of research interests should be detailed, ambitious, and realistic; it should present the highlights of your research journey objectively and professionally. By emphasizing previous experience, you can establish your suitability for undertaking projects. The document informs the committee of your track record and offers context regarding your interests by indicating the motivation and importance/relevance of previous studies. It also gives an overview or background of your subject, the strengths and limitations of your previous projects, and their relevance to future projects.

The document also establishes qualifications for a job position by illustrating your academic strengths and competencies, specialty, expertise, and compatibility with the faculty. It also demonstrates your ability to be innovative, think critically, and communicate as an academic or scholar. 

How Your Research Statement Should Look  

The statement is a formal document and should be formatted‌.

Your statement will typically be reviewed by scholars, academicians, and top administrative personnel within the faculty. The document must be written to appeal to the different categories of personnel.

You should incorporate the following formatting guidelines:

• Keep the length of the document at one or two pages (three if absolutely necessary). 
• Utilize headings and subheadings to categorize information. 
• Bullet points are also allowed to itemize details and points that do not require detailed explanations. 
• Ensure the font and font size you use are legible and the margins are enough to ensure the contents of your document do not appear clogged up or uneven. 

A research statement should be written in the third person (present tense) as it gives a sense of objectivity, not the first person, which can sometimes feel more personal than professional.

How to Structure a Research Statement

Your research statement demonstrates your intellectual integrity, capacity for success in an academic setting (including learning and teaching), and familiarity with the current research landscape. 

T o capture this information, you can follow the steps discussed below when planning what to include in the document; 

Step 1: Write a summary of your research 

The first step is to undertake a detailed self-assessment of your interests, field of study, achievements, and importance. The self-assessment should include reviewing past and current projects, activities, publications, and presentations. You should then summarize your research and highlight the theme guiding your studies. Mention any significant areas that you would like to contribute to, any new ideas you have, and the main conclusions of your work. This section should get the reader excited and prepare them for what to expect in the document.  

Step 2: Include a brief history of your past research 

Secondly, you should discuss your past work . This section, which should include specific projects you have worked on and issues you are trying to solve, should be more detailed than the summary above. It offers a sense of consistency and allows the committee to determine the progress you have made in your work. Remember to keep the content as relevant as possible. 

Step 3: List major findings, outcomes, and implications 

Next, you should address your achievements. This section can either list the themes, projects, topics, or areas of focus you have worked on chronologically or by specific subheadings. You can outline the guiding questions of your project, methodologies used, findings, contribution to the field of study, outcomes such as publications, presentations, essays , reports, etc., and implications such as collaborations, awards, conferences, etc. 

Step 4: Discuss your current research

This section helps to highlight your interests, skill sets, and capabilities necessary for the job position. Here, you can explain why you were interested in this subject and list some of the citations on which you have based your work. This section gives you the opportunity to highlight the novelty of your work, and thus the value of your work to the field of study and how it contributes to the subject should be covered here.

You must briefly discuss the methodology you used and the findings in concrete terms. Any partnerships with third parties and any funding you may have received for your work should be highlighted here. Include professional engagements, upcoming conferences, and upcoming publications in this section as well. 

Step 5: Describe your future goals or plans 

Finally, you should also mention how your current and past research has prepared you for your future plans. Since you are applying for a faculty position, you should demonstrate a clear vision of your future plans. This should include information on the problem you intend to focus on, the relevance of the issues to the field of study, and your academic and professional goals for the next 3-5 years.

Also, mention how your interests and ambitions align with the department’s and institution’s needs. You can achieve this by determining the faculty’s most important needs and objectives, paying close attention to the faculty’s research profile, and choosing an appropriate study topic that most closely aligns with both their and your objectives. 

Step 6: Identify potential funding sources

Most institutions will want to know about any external funding you may be able to access, and it can be an incentive for them to accept your application. Therefore, you should mention any potential funding sources at your disposal. This can be discussed by providing relevant details of sources of funds, such as grants from private institutions, government agencies, academic organizations, foundations, etc., and any other sources of funding you may have. 

Important Considerations

The strength of your research statement might be the most important deciding element in your application. If it is adequate, it can help you secure the position.

Here are some things to consider when preparing your statement:

Avoid jargon 

Avoid using terms and phrases that may be too technical or unclear. Make the statement understandable for people outside your discipline.

Note that the recruiting committee will comprise individuals from different disciplines, and if they are to review your application impartially, they need to understand what you intend to communicate. 

Be realistic 

Make sure you do not exaggerate your skills. Try to focus on specific projects and problems that are within your competencies. You can accomplish this by having a clearly defined theme for your statement. Exclude any minor projects, and the focus should be on the key and most significant ideas. The more reasonable your expectations are, the better off you will be. Though it is fine to have lofty plans for the future, do not assume that you can achieve them all at once.

Include examples 

Provide examples of your achievements to demonstrate your skills. Focus on a few relevant successes using your own words.

Tangible examples include referencing resultant publications, presentations, professional engagements, etc.  

Be confident 

Make sure you write with confidence and believe in what you want to say. You should be confident in your skills, achievements, and future goals. Therefore, avoid vague statements and present yourself as a well-qualified applicant.  

Proofread 

Do not forget to edit your document, including all detailed references, to ensure everything is correct. Some important points to consider are proper citations and formatting ( spelling, punctuation, and grammar ). Be sure to read over what you have written several times and make the necessary corrections before sending it to another person for review.

Frequently Asked Questions

A research statement highlights a job applicant’s experience in research and how that makes them suitable for an academic position. This requires citing specific current, past, and future projects and mentioning specific details about the project. However, a CV emphasizes a job applicant’s educational and professional background to show that they are qualified for the positions being applied for. 

Yes. You should consider creating a longer version of your research statement to take to the interview. The statement can be five to fifteen pages long. It is needed because, during the interview, you may be asked to provide in-depth details such as an activity schedule, budget, human resource requirements, and other specifics, which you can include in the longer version, unlike the standard version. 

Yes. It is recommended that you mention potential eternal funding sources and previous funding. This can be any external source, from foundations to government institutions.

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How to write a research statement

What is a research statement?

A research statement is a brief document showing a person’s research achievements, current research activities, and plans for future research. It is usually between one to three pages long. A research statement is necessary because it helps whoever is reading it to know the academic and work orientation of the owner. For instance, a panel interviewing you for a job can conclude on your suitability or otherwise after perusing your research statement. It is therefore an important document that the researcher should craft optimally. An effectively written research statement should convey the following messages:

• What inspired you to undertake the research
• The procedures you used to undertake the study
• The source of funding for your research
• If the research objectives were met
• The usefulness of your research to your discipline, profession, and society as a whole
• Any obstacles you faced during the research and how you tackled them
• How your research can be built upon by future studies
• Your current research effort
• Your short, medium, and long-term research plans

Why do you need a research statement?

If you are a job seeker or looking to apply for some post-graduate programs, you have to keep a research statement on standby in case the selectors ask for it. Your research statement helps the audience to

• Have an insight into your level of intellectual and professional development and accomplishments (and hence determine whether to accept or reject your application)
• Determine the most ideal roles for you if you are a job seeker
• Determine the appropriate supervisor for you if you are a graduate student
• Determine the nature or type of funding you’ll require

The following tips will help you write a winning research statement.

Focus on the subject matter

The topic here is research so be sure to focus on it. Each stage of the presentation should revolve around the main thesis of the paper which is a holistic articulation of your previous, present, and projected research. You have to realize that this is not a personal statement which is broader in scope and allows you to discuss from a variety of perspectives.

Keep it simple and short

Since this is just a summary of your research profile, there is no need to write excessively. Moreover, the selectors may have several other statements to go through as well. Though research can be technical to describe, endeavour to keep things as simple as possible without negating the technicalities. However, simplicity should not be misinterpreted as mediocrity, so try to make your document as intellectually robust as possible in terms of things like organization, logic, and sentence construction.

Write convincingly

You would have achieved nothing if your presentation is deemed hollow and unconvincing. The purpose is to either get the job or that PhD opportunity you crave for. Therefore, you must have the ability to communicate effectively.  If you are describing how your research objectives were accomplished, for example, you have to clearly, concisely, and logically demonstrate the steps you went through to achieve these objectives.

Be visionary but modest

This area mainly has to do with your future research proposals. They have to be articulated based on an idea of the kind of future you envisage as well as how your research efforts then will help provide solutions to problems you expect to emerge at that time. However, this has to be written with an air of modesty, bearing in mind that the future is uncertain and that your research projections can be altered by unfolding social dynamics.

Write what you can defend

You should bear in mind that the panel of selectors may throw a few questions at you on interview day. This should be one of your considerations when preparing your paper and reinforces the need for a not so lengthy paper that you can study more easily and memorize very well.

Proofread and edit your paper

This is one of the most important areas to consider when trying to craft a successful research statement. After investing your time and energy to prepare a competitive paper, you do not want typing, grammar, and formatting errors to make you look unserious and amateurish. Try and cross every “t” and dot every “i” since you may not get a second chance to make a first impression. You can engage friends and colleagues to help out in this regard if necessary.

Make suggestions about funding

Be sure to suggest some viable sources of external funding for your future research. Also indicate whether you have leveraged research grants or funds previously.

Research statement format

• Should not exceed three pages in length, preferably one or two.
• Fonts should be large and clear enough for easy reading
• Include informative headings and subheadings
• Pages should be numbered
• Include bullet points to enhance clarity
• Use reasonably sized margins

A research statement is a necessary condition for some academic programs and job offers. The aim is for the student or job applicant to present his previous and present research experience as well as his future research plans to a panel, board, or committee of selectors with the hope of ultimately scaling through. It is therefore important to craft a unique, winning statement that can stand out in the midst of competition and achieve the intended purpose.

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Center for Nuclear Security Science and Policy Initiatives

Texas A&M Engineering Experiment Station

Research Accomplishments

NSSPI is at the forefront of innovative research on all aspects of nuclear safeguards, security, and nonproliferation.  The following is a list of some of our major research accomplishments.

Became the first university research team to mount and record radiation data from a crane used in port operations.

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Designed the Self-Interrogation Neutron Resonance Densitometry (SINRD) detector for nuclear safeguards measurements with Los Alamos National Laboratory for testing by the IAEA.

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Developed the SHIELD framework to interdict HEU at borders.

Made the first quantitative measurement of Pu in used nuclear fuel with Oak Ridge National Laboratory.

Developed capability for bench-scale PUREX reprocessing of plutonium for nuclear forensics applications

Developed the PRAETOR tool and a latency method for proliferation risk analysis.

Performed nuclear forensics analysis on weapons-grade plutonium samples employing PUREX combined with ICPMS and gamma spectrometry

Devised a safeguards system concept for pebble-fueled high temperature gas-cooled reactors.

Developed a new technique for analyzing Pu K x-rays for nuclear forensics applications using a bent-crystal spectrometer.

Performed proliferation resistance / safeguards analysis of the Fast Breeder Reactor fuel cycle.

Developed a portable gamma radiation portal monitor specifically designed for the scanning of livestock.

Devised a methodology for determining which states will go nuclear

Performed innovative N-terrorism pathways analysis to boost the efficacy of defense.

Developed dynamic agent-based modeling using the Bayesian framework for addressing intelligent adaptive nuclear nonproliferation analysis.

Produced a significant number of graduate students with M.S., M.E., and Ph.D. degrees in NSSPI-centered research, with many other graduate students supported in other areas and disciplines.

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FREE 9+ Research Accomplishment Report Samples in PDF

One of the integral steps on a research journey is selecting a question and the right methods to answer it. There is a wide array of relevant topics that will greatly help you in selecting a question and get started on the methods side of your research. If you are a graduate student or a new researcher, you might be experiencing some challenges in your work such as several abstractions, complex language, and concepts. But, don’t worry because in this article, we have some informative guide and downloadable research accomplishment report templates to guide you in carefully managing and keeping track of the progress of your research project. Keep on reading!

Research Accomplishment Report

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A research accomplishment report is a fundamental document that demonstrates the overall performance and progress made toward accomplishing the definite goals and objectives in the research project. It is typically used by academic researchers, scientific researchers, and other kinds of researchers exclusively in monitoring the progress of their respective research projects and measuring their research skills and capabilities when it comes to fulfilling different kinds of research activities and other tasks. 

In order to maintain the right structure and processes inside the business firm and your research and development department, you need to write a clear and well-detailed accomplishment report of your research work. If writing a report is not your expertise, don’t worry and cut the mustard because we provide you some easy-to-follow tips that indicate how to write a research accomplishment report : 

First, you need to start your research accomplishment report with a clear and well-detailed summary which comprises your previous and current research project completions. Write your activities, tasks, roles and responsibilities, beneficial skills and competencies, goals, objectives, and many others concerning your research work. 

The second step in your research accomplishment report writing is to add more details for clear interpretation of your previous and current accomplishments in the summary section. Explain each aspect and highlight the significance of your research project, skill, and many more that you have contributed to help the company develop and advance.  

Then, you need to present a comprehensive time period of your research accomplishments by using a bulleted list or visual diagrams as you demonstrate the individual time period of each of your previous and current work accomplishments. 

Lastly, you need to tell about your research performance goals and expectations if you consider applying to a new company. Some examples of performance goals are examining the validity and truth of arguments prior to making conclusions, adopting technologies that assist in providing solutions, searching for different innovative approaches to a situation, and many other goals. While some examples of expectations are manifestations of a positive and respectful attitude, professionalism, etc.

A daily accomplishment report is a record of a particular employee’s performance or activities, and work accomplishments throughout the day. It can be stored and managed digitally and it must be submitted to the team leader or project manager thru email.

An annual accomplishment report is a document that provides a simple and concise summary of the accomplishments for the year. It contains essential information about work achievements that are achieved for the entire year.

When you create a summary of your accomplishments, think about your current and previous accomplishments that you have done. List them according to the dates. Make sure that the work accomplishments must be connected to the duties listed in a specific job advertisement that you want to apply. Then, quantify your work by providing an estimate or range. 

Some ways to describe your achievements are to quantify your achievements by utilizing numbers, percentages, and statistics or you can describe a qualitative achievement, and using your employer’s language. Additionally, you need to consider showcasing the achievements which are significant to the job requirements. 

Although the research work might not be a collaborative effort, you can be certain that conducting your research alone will help you exercise and enhance your creativity. However, if you feel easily overwhelmed by the scientific theory, practice, and execution of your research project, remember that “two heads is better than one” and try your best to involve other researchers. So, here are some of our downloadable and printable samples of accomplishment reports for your research, available in different kinds of formats. Simply click the research accomplishment report templates in this article and start downloading now!

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Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

Jeffrey braithwaite.

1 Australian Institute of Health Innovation, Macquarie University, North Ryde, New South Wales, Australia

Jessica Herkes

Kate churruca, janet c long, chiara pomare, claire boyling, mia bierbaum, robyn clay-williams, frances rapport, anne hogden, louise a ellis, kristiana ludlow, elizabeth austin, rebecca seah, elise mcpherson, peter d hibbert.

2 Division of Health Sciences, University of South Australia, Adelaide, South Australia, Australia

Johanna Westbrook

Associated data.

bmjopen-2018-025320supp001.pdf

bmjopen-2018-025320supp002.pdf

bmjopen-2018-025320supp003.pdf

Effective researcher assessment is key to decisions about funding allocations, promotion and tenure. We aimed to identify what is known about methods for assessing researcher achievements, leading to a new composite assessment model.

We systematically reviewed the literature via the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols framework.

Data sources

All Web of Science databases (including Core Collection, MEDLINE and BIOSIS Citation Index) to the end of 2017.

Eligibility criteria

(1) English language, (2) published in the last 10 years (2007–2017), (3) full text was available and (4) the article discussed an approach to the assessment of an individual researcher’s achievements.

Data extraction and synthesis

Articles were allocated among four pairs of reviewers for screening, with each pair randomly assigned 5% of their allocation to review concurrently against inclusion criteria. Inter-rater reliability was assessed using Cohen’s Kappa (ĸ). The ĸ statistic showed agreement ranging from moderate to almost perfect (0.4848–0.9039). Following screening, selected articles underwent full-text review and bias was assessed.

Four hundred and seventy-eight articles were included in the final review. Established approaches developed prior to our inclusion period (eg, citations and outputs, h-index and journal impact factor) remained dominant in the literature and in practice. New bibliometric methods and models emerged in the last 10 years including: measures based on PageRank algorithms or ‘altmetric’ data, methods to apply peer judgement and techniques to assign values to publication quantity and quality. Each assessment method tended to prioritise certain aspects of achievement over others.

Conclusions

All metrics and models focus on an element or elements at the expense of others. A new composite design, the Comprehensive Researcher Achievement Model (CRAM), is presented, which supersedes past anachronistic models. The CRAM is modifiable to a range of applications.

Strengths and limitations of this study

• A large, diverse dataset of over 478 articles, containing many ideas for assessing researcher performance, was analysed.
• Strengths of the review include executing a wide-ranging search strategy, and the consequent high number of included articles for review; the results are limited by the literature itself, for example, new metrics were not mentioned in the articles, and therefore not captured in the results.
• A new model combining multiple factors to assess researcher performance is now available.
• Its strengths include combining quantitative and qualitative components in the one model.
• The Comprehensive Researcher Achievement Model, despite being evidence oriented, is a generic one and now needs to be applied in the field.

Introduction

Judging researchers’ achievements and academic impact continues to be an important means of allocating scarce research funds and assessing candidates for promotion or tenure. It has historically been carried out through some form of expert peer judgement to assess the number and quality of outputs and, in more recent decades, citations to them. This approach requires judgements regarding the weight that should be assigned to the number of publications, their quality, where they were published and their downstream influence or impact. There are significant questions about the extent to which human judgement based on these criteria is an effective mechanism for making these complex assessments in a consistent and unbiased way. 1–3 Criticisms of peer assessment, even when underpinned by relatively impartial productivity data, include the propensity for bias, inconsistency among reviewers, nepotism, group-think and subjectivity. 4–7

To compensate for these limitations, approaches have been proposed that rely less on subjective judgement and more on objective indicators. 3 8–10 Indicators of achievement focus on one or a combination of four aspects: quantity of researcher outputs ( productivity ); value of outputs ( quality ); outcomes of research outputs ( impact ); and relations between publications or authors and the wider world ( influence ). 11–15 Online publishing of journal articles has provided the opportunity to easily track citations and user interactions (eg, number of article downloads) and thus has provided a new set of indices against which individual researchers, journals and articles can be compared and the relative worth of contributions assessed and valued. 14 These relatively new metrics have been collectively termed bibliometrics 16 when based on citations and numbers of publications, or altmetrics 17 when calculated by alternative online measures of impact such as number of downloads or social media mentions. 16

The most established metrics for inferring researcher achievement are the h-index and the journal impact factor (JIF). The JIF measures the average number of citations of an article in the journal over the previous year, and hence is a good indication of journal quality but is increasingly regarded as a primitive measure of quality for individual researchers. 18 The h-index, proposed by Hirsch in 2005, 19 attempts to portray a researcher’s productivity and impact in one data point. The h-index is defined as the number ( h ) of articles published by a researcher that have received a citation count of at least h. Use of the h-index has become widespread, reflected in its inclusion in author profiles on online databases such as Google Scholar and Scopus.

Also influenced by the advent of online databases, there has been a proliferation of other assessment models and metrics, 16 many of which purport to improve on existing approaches. 20 21 These include methods that assess the impact of articles measured by: downloads or online views received, practice change related to specific research, take-up by the scientific community or mentions in social media.

Against the backdrop of growth in metrics and models for assessing researchers’ achievements, there is a lack of guidance on the relative strengths and limitations of these different approaches. Understanding them is of fundamental importance to funding bodies that drive the future of research, tenure and promotion committees and more broadly for providing insights into how we recognise and value the work of science and scientists, particularly those researching in medicine and healthcare. This review aimed to identify approaches to assessing researchers’ achievements published in the academic literature over the last 10 years, considering their relative strengths and limitations and drawing on this to propose a new composite assessment model.

Search strategy

All Web of Science databases (eight in total, including the Web of Science Core Collection, MEDLINE and BIOSIS Citation Index) were searched using terms related to researcher achievement ( researcher excellence, track record, researcher funding, researcher perform*, relative to opportunity, researcher potential, research* career pathway, academic career pathway, funding system, funding body, researcher impact, scientific* productivity, academic productivity, top researcher, researcher ranking, grant application, researcher output, h*index, i*index, impact factor, individual researcher ) and approaches to its assessment ( model, framework, assess*, evaluat*, *metric*, measur*, criteri*, citation*, unconscious bias, rank* ) with ‘*’ used as an unlimited truncation to capture variation in search terms, as seen in online supplementary appendix 1 . These two searches were combined (using ‘ and ’), and results were downloaded into EndNote, 22 the reference management software.

Supplementary data

Study selection.

After removing duplicate references in EndNote, articles were allocated among pairs of reviewers (MB–JL, CP–CB, KL–JH and KC-LAE) for screening against inclusion criteria. Following established procedures, 23 24 each pair was randomly assigned 5% of their allocation to review concurrently against inclusion criteria, with inter-rater reliability assessed using Cohen’s kappa (ĸ). The ĸ statistic was calculated for pairs of researchers, with agreement ranging from moderate to almost perfect (0.4848–0.9039). 25 Following the abstract and title screen, selected articles underwent full text review. Reasons for exclusion were recorded.

Inclusion criteria

The following inclusion criteria were operationalised: (1) English language, (2) published in the last 10 years (2007–2017), (3) full text for the article was available, and (4) the article discussed an approach to the assessment of an individual researcher’s achievements (at the researcher or singular output-level). The research followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols framework. 26 Empirical and non-empirical articles were included because many articles proposing new approaches to assessment, or discussing the limitations of existing ones, are not level one evidence or research based. Both quantitative and qualitative studies were included.

Data extraction

Data from the included articles were extracted, including: the country of article origin, the characteristics of the models or metrics discussed, the perspective the article presented on the metric or model (positive, negative and indeterminable) including any potential benefits or limitations of the assessment model (and if these were perceived or based on some form of evidence). A customised data extraction sheet was developed in Microsoft Excel, trialled among members of the research team and subsequently refined. This information was synthesised for each model and metric identified through narrative techniques. The publication details and classification of each paper are contained in online supplementary appendix 2 .

Appraisal of the literature

Due to the prevalence of non-empirical articles in this field (eg, editorial contributions and commentaries), it was determined that a risk of bias tool such as the Quality Assessment Tool could not be applied. 27 Rather, assessors were trained in multiple meetings (24 October, 30 October and 13 November 2017) to critically assess the quality of articles. Given the topic of the review (focusing on the publication process), the type of models and metrics identified (ie, more metrics that use publication data metrics) may influence the cumulative evidence and subsequently create a risk of bias. In addition, three researchers (JH, EM and CB) reviewed every included article to extract documented conflicts of interests of authors.

Patient and public involvement

Patients and the public were not involved in this systematic review.

The final dataset consisted of 478 academic articles. The data screening process is presented in figure 1 .

Data screening and extraction process for academic articles.

Of the 478 included papers (see online supplementary appendix 2 for a summary), 295 (61.7%) had an empirical component, which ranged from interventional studies that assessed researcher achievement as an outcome measure (eg, a study measuring the outcomes of a training programme), 28 as a predictor 29–31 (eg, a study that demonstrated the association between number of citations early in one’s career and later career productivity) or reported a descriptive analysis of a new metric. 32 33 One hundred and sixty-six (34.7%) papers were not empirical, including editorial or opinion contributions that discussed the assessment of research achievement, or proposed models for assessing researcher achievement. Seventeen papers (3.6%) were reviews that considered one or more elements of assessing researcher achievements. The quality of these contributions ranged in terms of the risk of bias in the viewpoint expressed. Only for 19 papers (4.0%) did the authors declare a potential conflict of interest.

Across the study period, 78 articles (16.3%) involved authors purporting to propose new models or metrics. Most articles described or cited pre-existing metrics and largely discussed their perceived strengths and limitations. Figure 2 shows the proportion of positive or negative discussions of five of the most common approaches to assessing an individual’s research achievement (altmetrics, peer-review, h-index, simple counts and JIF). The approach with most support was altmetrics (51.0% of articles mentioning altmetrics). The JIF was discussed with mostly negative sentiments in relevant articles (69.4%).

Percentages of positive and negative discussion regarding selected commonly used metrics for assessing individual researchers (n=478 articles). Positive discussion refers to articles that discuss the metric in favourable light or focus on the strengths of the metric; negative discussion refers to articles that focus on the limitations or shortcomings of the metric. JIF, journal impact factor.

Citation-based metrics

Publication and citation counts.

One hundred and fifty-three papers (32.0%) discussed the use of publication and citation counts for purposes of assessing researcher achievement, with papers describing them as a simple ‘traditional but somewhat crude measure’, 34 as well as the building blocks for other metrics. 35 A researcher’s number of publications, commonly termed an n-index, 36 was suggested by some to indicate researcher productivity, 14 rather than quality, impact or influence of these papers. 37 However, the literature suggested that numbers of citations indicated the academic impact of an individual publication or researcher’s body of work, calculated as an author’s cumulative or mean citations per article. 38 Some studies found support for the validity of citation counts and publications in that they were correlated with other indications of a researcher’s achievement, such as awards and grant funding, 39 40 and were predictive of long-term success in a field. 41 For example, one paper argued that having larger numbers of publications and being highly cited early in one’s career predicted later high-quality research. 42

A number of limitations of using citation or publication counts was observed. For example, Minasny et al 43 highlighted discrepancies between publications and citations counts in different databases because of their differential structures and inputs. 43 Other authors 38 44 45 noted that citation patterns vary by discipline, which they suggested can make them inappropriate for comparing researchers from different fields. Average citations per publication were reported as highly sensitive to change or could be skewed if, for example, a researcher has one heavily cited article. 46 47 A further disadvantage is the lag-effect of citations 48 49 and that, in most models, citations and publications count equally for all coauthors despite potentially differential contributions. 50 Some also questioned the extent to which citations actually indicated quality or impact, noting that a paper may influence clinical practice more than academic thinking. 51 Indeed, a paper may be highly cited because it is useful (eg, a review), controversial or even by chance, making citations a limited indication of quality or impact. 40 50 52 In addition to limitations, numerous authors made the point that focusing on citation and publication counts can have unintended, negative consequences for the assessment of researcher achievement, potentially leading to gaming and manipulation, including self-citations and gratuitous authorship. 53 54

Singular output-level approaches

Forty-one papers (8.6%) discussed models and metrics at the singular output or article-level that could be used to infer researcher achievement. The components of achievement they reported assessing were typically quality or impact. 55 56 For example, some papers reported attempts to examine the quality of a single article by assessing its content. 57 58 Among the metrics identified in the literature, the immediacy index focused on impact by measuring the average number of cites an article received in the year it was published. 59 Similarly, Finch 21 suggested adapting the Source Normalized Impact per Publication (a metric used for journal-level calculations across different fields of research) to the article-level.

Many of the article-level metrics identified could also be upscaled to produce researcher-level indications of academic impact. For example, the sCientific currENcy Tokens (CENTs), proposed by Szymanski et al 60 involved giving a ‘cent’ for each new non-self-citation a publication received; CENTs are then used as the basis for the researcher-level i-index, which follows a similar approach as the h-index but removes self-citations. 60 The temporally averaged paper-specific impact factor calculates an article’s average number of citations per year combined with bonus cites for the publishing journal’s prestige and can be aggregated to measure the overall relevance of a researcher (temporally averaged author-specific impact factor). 61

Journal impact factor

The JIF, commonly recognised as a journal-level measure of quality, 59 62 was discussed in 211 (44.1%) of the papers reviewed in relation to assessing singular outputs or individual researchers. A number of papers described the JIF being used informally to assess an individual’s research achievement at the singular output-level and formally in countries such as France and China. 63 It implies article quality because it is typically a more competitive process to publish in journals with high impact factors. 64 Indeed, the JIF was found to be the best predictor of a paper’s propensity to receive citations. 65

The JIF has a range of limitations when used to indicate journal quality, 66 including that it is disproportionally affected by highly cited, outlier articles 41 67 and is susceptible to ‘gaming’ by editors. 17 68 Other criticisms focused on using the JIF to assess individual articles or the researchers who author them. 69 Some critics claimed that using the JIF to measure an individual’s achievement encourages researchers to publish in higher impact but less appropriate journals for their field, which ultimately means their article may not be read by relevant researchers. 70 71 Furthermore, the popularity of a journal was argued to be a poor indication of the quality of any one article, with the citation distributions for calculating JIF found to be heavily skewed (ie, a small subset of papers receive the bulk of the citations, while some may receive none). 18 Ultimately, many commentators argued that the JIF is an inappropriate metric to assess individual researchers because it is an aggregate metric of a journal’s publication and expresses nothing about any individual paper. 21 49 50 72 However, Bornmann and Pudovkin 73 suggested one case in which it would be appropriate to use JIF for assessing individual researchers: in relation to their recently published papers that had not had the opportunity to accumulate citations. 73

Researcher-level approaches

The h-index was among the most commonly discussed metrics in the literature (254 [53.1%] of the papers reviewed); in many of these papers, it was described by authors as more sophisticated than citation and publication counts but still straightforward, logical and intuitive. 74–76 Authors noted its combination of productivity (h publications) and impact indicators (h citations) as being more reliable 77 78 and stable than average citations per publications, 41 because it is not skewed by the influence of one popular article. 79 One study found that the h-index correlated with other metrics more difficult to obtain. 76 It also showed convergent validity with peer-reviewed assessments 80 and was found to be a good predictor of future achievement. 41

However, because of the lag-effect with citations and publications, the h-index increases with a researcher’s years of activity in the field, and cannot decrease, even if productivity later declines. 81 Hence, numerous authors suggested it was inappropriate for comparing researchers at different career stages, 82 or those early in their career. 68 The h-index was also noted as being susceptible to many of the critiques levelled against citation counts, including potential for gaming and inability to reflect differential contributions by coauthors. 83 Because disciplines differ in citation patterns, 84 some studies noted variations in author h-indices between different methodologies 85 and within medical subspecialties. 86 Some therefore argued that the h-index should not be used as the sole measure of a researcher’s achievement. 86

h-Index variants

A number of modified versions of the h-index were identified; these purported to draw on its basic strengths of balancing productivity with impact while redressing perceived limitations. For example, the g-index measures global citation performance 87 and was defined similarly to the h-index but with more weight given to highly cited articles by assuming the top g articles have received at least g 2 citations. 88 Azer and Azer 89 argued it was a more useful measure of researcher productivity. 89 Another variant of the h-index identified, the m-quotient, was suggested to minimise the potential to favour senior academics by accounting for the time passed since a researcher has begun publishing papers. 90 91 Other h-index variations reported in the articles reviewed attempted to account for author contributions, such as the h-maj index, which includes only articles in which the researcher played a core role (based on author order), and the weighted h-index, which assigns credit points according to author order. 87 92

Recurring issues with citation-based metrics

The literature review results suggested that no one citation-based metric was ideal for all purposes. All of the common metrics examined focused on one aspect of an individual’s achievement and thus failed to account for other aspects of achievement. The limitations with some of the frequently used citation-based metrics are listed in box 1 .

Common limitations in the use of citation-based metrics

• Challenges with reconciling differences in citation patterns across varying fields of study.
• Time-dependency issues stemming from differences in career length of researchers.
• Prioritising impact over merit, or quality over quantity, or vice versa.
• The lag-effect of citations.
• Gaming and the ability of self-citation to distort metrics.
• Failure to account for author order.
• Contributions from authors to a publication are viewed as equal when they may not be.
• Perpetuate ‘publish or perish’ culture.
• Potential to stifle innovation in favour of what is popular.

Non-citation-based approaches

In contradistinction with the metrics discussed above, 54 papers (11.3%) discussed altmetrics (or ‘alternative metrics’), which included a wide range of techniques to measure non-traditional, non-citation based usage of articles, that is, influence. 17 Altmetric measures included the number of online article views, 93 bookmarks, 94 downloads, 41 PageRank algorithms 95 and attention by mainstream news, 63 in books 96 and social media, for example, in blogs, commentaries, online topic reviews or Tweets. 97 98 These metrics typically measure the ‘web visibility’ of an output. 99 A notable example is the social networking site for researchers and scientists, ResearchGate, which uses an algorithm to score researchers based on the use of their outputs, including citations, reads and recommendations. 100

A strength of altmetrics lies in providing a measure of influence promptly after publication. 68 101 102 Moreover, altmetrics allows tracking of the downloads of multiple sources (eg, students, the general public, clinicians, as well as academics) and multiple types of format (eg, reports and policy documents), 103 which are useful in gauging a broader indication of impact or influence, compared with more traditional metrics that solely or largely measure acknowledgement by experts in the field through citations. 17

Disadvantages noted in the articles reviewed included that altmetrics calculations have been established by commercial enterprises such as Altmetrics LLC (London, UK) and other competitors, 104 and there may be fees levied for their use. The application of these metrics has also not been standardised. 96 Furthermore, it has been argued that, because altmetrics are cumulative and typically at the article-level, they provide more an indication of influence or even popularity, 105 instead of quality or productivity. 106 Hence, one study suggested no correlation between attention on Twitter and expert analysis of an article’s originality, significance or rigour. 107 Another showed that Tweets predict citations. 108 Overall, further work needs to assess the value of altmetric scores in terms of their association with other traditional indicators of achievement. 109 Notwithstanding this, there were increasing calls to consider altmetrics alongside more conventional metrics in assessing researchers and their work. 110

Past funding

A past record of being funded by national agencies was identified as a common measurement of individual academic achievement (particularly productivity, quality and impact) in a number of papers and has been argued to be a reliable method that is consistent across medical research. 111–113 For example, the National Institute of Health’s (NIH) Research Portfolio Online Reporting Tools system encourages public accountability for funding by providing online access to reports, data and NIH-funded research projects. 111 114

New metrics and models identified

The review also identified and assessed new metrics and models that were proposed during the review period, many of which had not gained widespread acceptance or use. While there was considerable heterogeneity and varying degrees of complexity among the 78 new approaches identified, there were also many areas of overlap in their methods and purposes. For example, some papers reported on metrics that used a PageRank algorithm, 115 116 a form of network analysis based on structural characteristics of publications (eg, coauthorship or citation patterns). 14 Metrics based on PageRank purported to measure both the direct and indirect impacts of a publication or researcher. Other approaches considered the relative contributions of authors to a paper in calculating productivity. 117 Numerous metrics and models that built on existing approaches were also reported. 118 For example, some developed composite metrics that included a publication’s JIF alongside an author contribution measure 119 or other existing metrics. 120 However, each of these approaches reported limitations, in addition to their strengths or improvements on other methods. For example, in focusing on productivity, a metric necessarily often neglected impact. 121 Online supplementary appendix 3 provides a summary of these new or refashioned metrics and models, with details of their basis and purpose.

This systematic review identified a large number of diverse metrics and models for assessing an individual’s research achievement that have been developed in the last 10 years (2007–2017), as evidenced in online supplementary appendix 3 . At the same time, other approaches that pre-dated our study time period of 2007–2017 were also discussed frequently in the literature reviewed, including the h-index and JIF. All metrics and models proposed had their relative strengths, based on the components of achievement they focused on, and their sophistication or transparency.

The review also identified and assessed new metrics emerging over the past few decades. Peer-review has been increasingly criticised for reliance on subjectivity and propensity for bias, 7 and there have been arguments that the use of specific metrics may be a more objective and fair approach for assessing individual research achievement. However, this review has highlighted that even seemingly objective measures have a range of shortcomings. For example, there are inadequacies in comparing researchers at different career stages and across disciplines with different citation patterns. 84 Furthermore, the use of citation-based metrics can lead to gaming and potential ethical misconduct by contributing to a ‘publish or perish’ culture in which researchers are under pressure to maintain or improve their publication records. 122 123 New methods and adjustments to existing metrics have been proposed to explicitly address some of these limitations; for example, normalising metrics with ‘exchange rates’ to remove discipline-specific variation in citation patterns, thereby making metric scores more comparable for researchers working in disparate fields. 124 125 Normalisation techniques have also been used to assess researchers’ metrics with greater recognition of their relative opportunity and career longevity. 126

Other criticisms of traditional approaches centre less on how they calculated achievement and more on what they understood or assumed about its constituent elements. In this review, the measurement of impact or knowledge gain was often exclusively tied to citations. 127 Some articles proposed novel approaches to using citations as a measure of impact, such as giving greater weight to citations from papers that were themselves highly cited 128 or that come from outside the field in which the paper was published. 129 However, even other potential means of considering scientific contributions and achievement, such as mentoring, were still ultimately tied to citations because mentoring was measured by the publication output of mentees. 130

A focus only on citations was widely thought to disadvantage certain types of researchers. For example, researchers who aim to publish with a focus on influencing practice may target more specialised or regional journals that do not have high JIFs, where their papers will be read by the appropriate audience and findings implemented, but they may not be well cited. 51 In this regard, categorising the type of journal in which an article has been published in terms of its focus (eg, industry, clinical and regional/national) may go some way towards recognising those publications that have a clear knowledge translation intention and therefore prioritise real-world impact over academic impact. 122 There were only a few other approaches identified that captured broader conceptualisations of knowledge gain, such as practical impact or wealth generation for the economy, and these too were often simplistic, such as including patents and their citations 131 or altmetric data. 96 While altmetrics hold potential in this regard, their use has not been standardised, 96 and they come with their own limitations, with suggestions that they reflect popularity more so than real-world impact. 105 Other methodologies have been proposed for assessing knowledge translation and real-world impact, but these can often be labour intensive. 132 For example, Sutherland et al 133 suggested that assessing individual research outputs in light of specific policy objectives through peer-review based scoring, may be a strategy, but this is typically not feasible in situations such as grant funding allocation, where there are time constraints and large applicant pools to assess.

In terms of how one can make sense of the validity of many of these emerging approaches for assessing an individual’s research achievements, metrics should demonstrate their legitimacy empirically, as well as having a theoretical basis for their use and clearly differentiating what aspects of quality, achievement or impact they purport to examine. 55 65 If the recent, well-publicised 134–136 San Francisco Declaration on Research Assessment 137 is anything to go by, internationally, there is a move away from the assessment of individual researchers using the JIF and the journal in which the research has been published.

There is momentum, instead, for assessment of researcher achievements on the basis of a wider mix of measures, hence our proposed Comprehensive Researcher Achievement Model (CRAM) ( figure 3 ). On the left-hand side of this model is the researcher to be assessed and key characteristics that influence the assessment. Among these factors, some (ie, field or discipline, coauthorship and career longevity) can be controlled for depending on the metric, while other components, such as gaming or the research topic (ie, whether it is ‘trendy’ or innovative), are less amenable to control or even prediction. Online databases, which track citations and downloads and measure other forms of impact, hold much potential and will likely be increasingly used in the future to assess both individual researchers and their outputs. Hence, assessment components (past funding, articles, citations, patents, downloads and social media traction) included in our model are those primarily accessible online.

The Comprehensive Researcher Achievement Model.

Strengths and limitations

The findings of this review suggest assessment components should be used with care, with recognition of how they can be influenced by other factors, and what aspects of achievement they reflect (ie, productivity, quality, impact and influence). No metric or model singularly captures all aspects of achievement, and hence use of a range, such as the examples in our model, is advisable. CRAM recognises that the configuration and weighting of assessment methods will depend on the assessors and their purpose, the resources available for the assessment process and access to assessment components. Our results must be interpreted in light of our focus on academic literature. The limits of our focus on peer-reviewed literature were evident in the fact that some new metrics were not mentioned in articles and therefore not captured in our results. While we defined impact broadly at the outset, overwhelmingly, the literature we reviewed focused on academic, citation-based impact. Furthermore, although we assessed bias in the ways documented, the study design limited our ability to apply a standardised quality assessment tool. A strength of our focus was that we set no inclusion criteria with regard to scientific discipline, because novel and useful approaches to assessing research achievement can come from diverse fields. Many of the articles we reviewed were broadly in the area of health and medical research, and our discussion is concerned with the implications for health and medical research, as this is where our interests lie.

There is no ideal model or metric by which to assess individual researcher achievement. We have proposed a generic model, designed to minimise risk of the use of any one or a smaller number of metrics, but it is not proposed as an ultimate solution. The mix of assessment components and metrics will depend on the purpose. Greater transparency in approaches used to assess achievement including their evidence base is required. 37 Any model used to assess achievement for purposes such as promotion or funding allocation should include some quantitative components, based on robust data, and be able to be rapidly updated, presented with confidence intervals and normalised. 37 The assessment process should be difficult to manipulate and explicit about the components of achievement being measured. As such, no current metric suitably fulfils all these criteria. The best strategy to assess an individual’s research achievement is likely to involve the use of multiple approaches 138 in order to dilute the influence and potential disadvantages of any one metric while providing more rounded picture of a researcher’s achievement 83 139 ; this is what the CRAM aims to contribute.

All in all, achievement in terms of impact and knowledge gain is broader than the number of articles published or their citation rates and yet most metrics have no means of factoring in these broader issues. Altmetrics hold promise in complementing citation-based metrics and assessing more diverse notions of impact, but usage of this type of tool requires further standardisation. 96 Finally, despite the limitations of peer-review, the role of expert judgement should not be discounted. 41 Metrics are perhaps best applied as a complement or check on the peer-review process, rather than the sole means of assessment of an individual’s research achievements. 140

Supplementary Material

Contributors: JB conceptualised and drafted the manuscript, revised it critically for important intellectual content and led the study. JH, KC and JCL made substantial contributions to the design, analysis and revision of the work and critically reviewed the manuscript for important intellectual content. CP, CB, MB, RC-W, FR, PS, AH, LAE, KL, EA, RS and EM carried out the initial investigation, sourced and analysed the data and revised the manuscript for important intellectual content. PDH and JW critically commented on the manuscript, contributed to the revision and editing of the final manuscript and reviewed the work for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Funding: The work on which this paper is based was funded by the Australian National Health and Medical Research Council (NHMRC) for work related to an assessment of its peer-review processes being conducted by the Council. Staff of the Australian Institute of Health Innovation undertook this systematic review for Council as part of that assessment.

Disclaimer: Other than specifying what they would like to see from a literature review, NHMRC had no role in the conduct of the systematic review or the decision to publish.

Competing interests: None declared.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data sharing statement: All data have been made available as appendices.

Patient consent for publication: Not required.

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PhD application: Writing summary of accomplishments

[I am too much afraid to ask this question becuase I think most of you will say that I am too stupid to understand meaning of "Summary of Accomplishments".]

So, I am applying for a PhD position which is asking for "Summary of Accomplishments" letter. What things should be included in it?

Is it about my accomplishments other than my research work or research work itself is an accomplishment? I was teacher assistant in many courses, it is an accomplishment? Should it be written in a list form or in a paragraph form?

In short, what does "accomplishments" mean when PhD hiring committee ask for it?

I am asking this question here becuase I could not find any appropriate answer from Google.

• graduate-admissions

• I would advocate writing in proper sentences rather than a bullet point list in any formal writing. –  astronat supports the strike Commented Jun 25, 2018 at 16:05

2 Answers 2

In making any kind of application, applicants typically know what they want and why, whether the application is for admission to a program, for research support, or for a job.

However, in making this application (or others later), you should consider the reasons the program (funding agency, or employer) would want to select you. Then, within the bounds of reasonable modesty, you must go about the task of satisfying them as much as possible as to each of those reasons.

Specifically, what reasons might the PhD program to which you are applying have for accepting an applicant? Here are a few fairly obvious items. You may have information about your field or the specific program that would generate more items. But it is crucial for you to think about this application from their point of view.

(1) They want to be sure you have the necessary native ability, background in the field, and perseverance to do the work to finish your PhD in a reasonable length of time. Of course, they are allowed hope you will do important publishable research that will enhance the reputation of their program. So you should mention anything that involves success in your previous studies or allied intellectual pursuits. (@JaganMohan has listed some items.)

(2) Possibly they will be guaranteeing you some financial support. This may involve your being a teaching assistant (eventually possibly lecturer) or a research assistant. So you should mention any work you have done reading student homework or exams, any work helping students (US 'tutoring'), any proficiencies for literature searches for research projects, experience using relevant lab equipment, and anything that gives evidence of relevant computer or programming skills.

(3) Work toward a PhD is not for everyone who does reasonably well as a BS or MS student. Not everyone stays with it. They are limited as to how many people they can admit, and they'd prefer to admit people who can stand stiff competition, can successfully manage a demanding workload, and who do not get panicky or discouraged the first time things go wrong. So, mention of nonacademic jobs you did to help with expenses, and any long term projects you have finished (even if not exactly in your field).

It is probably best not to speak directly to their motivations. They know what they are looking for without your instruction. Simply give them information that will allow them to be satisfied on each point. Just lists of facts, don't exaggerate or psychoanalyze yourself. If something seems too much like bragging (especially something difficult to document), maybe one of your references can do the bragging for you.

Accomplishments that most potential employees, guides, student application reviewers, etc are looking for are positions, rewards, recognitions, etc that indicate achievements and are demonstrative of work culture, personal capability of setting and achieving goals, intellectual level, skill development, attitude and knowledge, specialization, tenacity, continuity, etc.

The rough rule of thumb is that 'anything won in a competition is an accomplishment'.

Accomplishment is also attainment of certain position or degree or diploma or certification gained through some labour, study, test or recognition.

Hope this helps.

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My scientific research began in the area of optical spectroscopy during my studies toward a Master of Science degree at Washington State University where I was a Fulbright scholar in 1969-71. I studied the optical spectra of rare earths in various crystals, with the goal of determining the energy levels of the electronic ground state configuration and explaining the observed fine structure by crystal electric field calculations.

My Ph. D. thesis at the Technical University in Munich, Germany, during 1971-74 involved Mössbauer spectroscopy on the magnetic coupling and spin relaxation of rare earth impurities in various non-magnetic metals. At the time, such coupling phenomena were of great interest i n conjunction with such topics as the RKKY coupling, the Kondo effect, and the existence of giant magnetic moments.

During my postdoc days at Lawrence Berkeley Laboratory (1975-77) I used photoemission spectroscopy in all its variants (XPS, UPS, ARPES, Ph.D.) with emphasis on angle resolved photoemission studies and band mapping of noble metals. I was fortunate to experience the early days of synchrotron radiation experiments at SSRL. This exciting time constituted the beginning of my long love of synchrotron radiation research, which to this day has remained my main scientific focus.

My independent scientific career started as a staff scientist at SSRL. Upon my arrival in 1977, I decided to work in the challenging soft x-ray region, which at the time was largely inaccessible, owing to the unavailability of ultra-smooth optics and the omnipresent carbon contamination on the optical elements in grating monochromators which depressed the photon flux in the 250 - 1000 eV range. In the 1000 - 2000eV range, where crystal monochromators can be used it was difficult to obtain monochromator crystals with suitable d-spacings which could withstand the incident x-ray power. Earlier synchrotron radiation research had therefore focused on the ultraviolet region below about 40 eV, where near normal incidence optics could be used, and on the x-ray region above 4 keV, where conventional monochromator crystals like Si were readily available and the radiation could be brought into air through berillium windows. My goal as a staff scientist at SSRL was to open up the soft x-ray region which provides access to the K absorption edges of the chemically important elements carbon, nitrogen, oxygen, aluminum, silicon, and sulfur, to the important L absorption edges of the 3d metals, especially the magnetic materials iron, cobalt and nickel, and the M edges of the rare earths.

The results in the graph below show the success of this effort. The left column demonstrates the progress that was made in the late '70s with the grazing incidence grating monochromator "grasshopper" to produce soft x-rays in the range above the carbon K-edge (280 eV). The first breakthrough came from using high quality mirrors. The second from cleaning the optics of carbon contamination. However, the flux still deteriorated with time because the intense synchrotron radiation cracked hydrocarbons and deposited them on the o ptics (Appl. Optics 19, 3911 (1980)). The right column demonstrates the results obtained with the first ultra high vacuum double crystal monochromator "Jumbo" in the early '80s (Nucl. Instr. Meth. 195, 115 (1982)). As as staff scientist I was responsible for both monochromators and led the team that built Jumbo. These monochromators at SSRL led to pioneering studies in the soft x-ray region by many groups and this work stimulated the planning for the high brightness Advance d Light Source (ALS) in Berkeley.

My research at SSRL (1977-81) and later at EXXON (1981-85) focused on the development of the surface EXAFS and NEXAFS techniques for the determination of the geometric arrangement and bonding of atoms, molecules and thin organic films on surfaces. These experiments concentrated on surface complexes formed by C, N, O and S atoms and molecules, which constitute the most important elements in catalytic reactions. In the process of developing reliable x-ray based techniques for surface investigations, I also explored photon stimulated ion desorption and later contributed to the development of x-ray emission spectroscopy for the atom-specific investigation of the surface chemical bond. At the IBM Almaden Research Center (1985-99) my surface science interests shifted to the study of orientation and relaxation phenomena at polym er surfaces, in particular, the origin of liquid crystal alignment on such surfaces. My interest in magnetism research was stimulated by the strong magnetism research programs at Almaden and by managing the Department of Magnetic Materials and Phenomena from 1991 to 1994. During that time I began to use soft x-rays for magnetic spectroscopy and spectro-microscopy of magnetic thin films and interfaces which constitutes the major part of my research program today. The studies are carried out with polarized soft x-ray synchrotron radiation which offers access to the most important L absorption edges of Fe, Co and Ni. Among the unique capabilities of such x-ray magnetic dichroism studies are their elemental, chemical and magnetic specificity and the ability of magnetic imaging with x-ray photoemission electron microscopy ( XPEEM ) , presently offering a lateral resolution of 20nm (2nm in the near future).

Below I will briefly discuss the main milestones and areas of scientific research, give examples of some work, and list the most important publications associated with my research efforts as an independent scientist.

1978: Introduction of the SEXAFS technique. A group at Bell Labs (in the hard x-ray range) and I (in the soft x-ray range, Phys. Rev. B18, 4132 (1 978) ) pioneered the surface extended x-ray absorption fine structure (SEXAFS) technique as a tool for exploring surface structures. Over the following years I developed SEXAFS from a conceptual into a powerful mature technique for the study of chemisorbed low-Z atoms such as C, N, O and S. Highlights of the work are given in Phys. Rev. Lett. 43, 1882 (1979), Surf. Science 117, 503 (1982), Phys. Rev. Lett. 49, 142 (1982) , Phys. Rev. Lett. 55, 1468 (1985) , and Surf. Science 177, 114 (1986). Todate SEXAFS has been used to determine more than 100 adsorbate geometries on surfaces. Only LEED has determined more surface structures. I have written a comprehensive review of the technique, published in "X-Ray Absorption: Principles, Applications, Techniques of EXAFS, SEXAFS and XANES", Edit. D. C. Koningsberger and R. Prins (Wiley, 1988).

1980-1983: Photon Stimulated Ion Desorption (PSID). During this time period I explored PSID from surfaces, following core electron excitation, as a structural tool ( Phys. Rev. Lett. 45, 1870 (1980) ), identified desorption mechanisms such as multielectron excitations ( Phys. Rev. Lett. 47, 1300 (1981) ), and x-ray induced electron stimulated desorption (Surf. Science 134, 547 (1983)).

1981: Introduction of the NEXAFS technique. After recording the first near edge x-ray absorption fine structure (NEXAFS) spectra of chemisorbed molecules (Phys. Rev. Lett. 47, 381 (1981) and Phys. Rev. B26, 4111 (1982) , I developed NEXAFS into a powerful technique for the study of simple and complex mo lecules bonded to surfaces and of thin organic films (polymers). I demonstrated that NEXAFS can determine the precise orientation of molecules on surfaces, their intra-molecular bond lengths and their bond hybridization. Today, NEXAFS has been employed to determine the molecular orientation and bond lengths of more than 200 molecular adsorption systems. From such studies we have learned how to link the molecular chemisorption geometry to the geometry and molecular orbital structure o f the free molecule. The technique is extensively covered in my monograph " NEXAFS Spectroscopy " which was published in 1992. Today NEXAFS is increasingly used for the study of polymer surfaces and thin films and in conjunction with microscopy, so called " spectro-microscopy " , for the study of polymers and biological macromolecules.

1994-1997: X-Ray emission spectroscopy of molecules bonded to surfaces. This work carried out at the Advanced Light Source (ALS) in Berkeley in collaboration with Anders Nilsson of Uppsala University (today a Professor at SSRL) established x-ray emission spectroscopy as a powerful new tool for the study of the surface chemical bond ( Phys. Rev. Lett. 78, 2847 (199 7) , Appl. Phys. A 65, 147 (1997) ). Systematic studies of a variety of chemisorption systems revealed a new atom based picture of the surface chemical bond, showing the inadequacy of conventional text book pictures. X-ray emission spectroscopy can be viewed as the experimental analogue of the Linear Combination of Atomic Orbitals (LCAO) scheme.

Element specific and polarization dependent XES spectra of glycine on Cu(110)

1996-present: The surface structure of polymers. This work utilizes surface sensitive NEXAFS spectroscopy to probe the alignment ( Macromolecules 31, 1942 (1998) ; ibid 34, 1128 (2001) ) and relaxation ( Macromolecules 30, 7768 (1997) ) of molecular groups at polymer surfaces. A highlight of this work is the solution of a 90-year-old puzzle, the origin of liquid crystal (LC) alignment on rubbed polymer films. Rubbing is an important technological process, used in flat panel displays to align LCs on the rubbed surface, yet the alignment process remained a puzzle ever since its discovery in 1906. NEXAFS work revealed the microscopic origin of the LC alignment process ( J. Elect. Spec. Rcl. Phenom. 98-99,189(1999 ), Science 292, 2299 (2001) ) and led to new materials (diamond-like carbon) and processes (ion beam irradiation) for use in tomorrow's flat panel displays ( Nature 411, 56 (2001) ). The scientific understanding provided by the NEXAFS work constituted not only a device enabling step but promises to redirect the $20 billion-per-year flat panel industry.

1991-present: Magnetic thin films and interfaces . This work utilizes polarized soft x-rays for the study of magnetic materials and phenomena, in particular the x-ray magnetic circular (XMCD) and linear (XMLD) dichroism techniques. Such studies have proven the existence of induced interfacial magnetic moments in non-magnetic films such as Cu, when adjacent to a ferromagnet ( Phys. Rev. Lett. 72, 1112 (1994) ), and more generally demonstrated the existence of enhanced and reduced moments in ultrathin magnetic films and their dependence on crystallographic structure (IBM. J. Res. Develop. 42, 73 (1998) ). Through a unique separation of spin and orbital moments, XMCD has provided an unprecedented clear picture of the origin of the magnetocrystalline anisotropy in thin film multilayers ( Ph ys. Rev. Lett. 75, 3748 (1995) ; Phys. Rev. Lett. 75, 3752 (1995) , J. Magn. Magn. Mater. 200, 470 (1999) ). Examples of XMCD studies are shown in the pictures below.

The XMCD and XMLD techniques can also be used for imaging. My work has provided the first ferromagnetic ( Science 259, 659 (1993) ) and antiferromagnetic ( Phys. Rev. Lett. 83, 1862 (1999) , Science 287, 1014 (2000) ) images with x-rays which are shown below.

The first magnetic i mages recorded with x-rays

Magnetic imaging with x-rays offers many advantages over conventional imaging techniques. By tuning the photon energy one can select different elements or layers, polarization control can distinguish between ferromagnetism and antiferromagnetism, and the limited sampling depth of electron yield detection opens the door for getting unique interfacial information for thin film multilayers. Below is a picture of recent results that combine antiferromagneti c and ferromagnetic imaging. It demonstrates how the antiferromagnetic domain structure of the clean NiO(100) surface changes upon Co deposition and how the ferromagnetic domain structure of Co follows that of NiO. Within each antiferromagnetic stripe domain there are two ferromagnetic Co domains with opposite spin directions, as illustrated in the icon of the figure.

Domai n structure in antiferromagnetic NiO and ferromagnetic Co deposited on top

Such x-ray photoemission electron microscopy (XPEEM) studies have provided significant new insight into interfacial magnetic phenomena such as exchange bias ( Nature 405, 767 (2000) ).

My present and future research topics are: exchange bias , spin injection , ultrafast switching and the development of coherent x-ray diffraction ( speckle ) for the study of nanoscale spin dynamics.

The next picture below illustrates how our studies have not only revealed the correspondence of the domain structure in an antiferromagnet and an adjacent ferromagnet, but were also able to determine the magnetic structure of the all important interface between them. Indeed, uncompensated spi ns at the interface hold the key to the exchange bias puzzle ( Phys. Rev. Lett. 87, 247201 (2001) ; Phys. Rev. Lett. 91, 017203 (2003) ). Some of them are anchored in the antiferromagnet ( Phys. Rev. Lett. 92, 247201 (2004) ) and their direction is therefore pinned in space. They give rise to the exchange bias effect. A more detailed discussion of the topic of exchange bias is given under Research Programs and under Highlights on the home page.

Artist's rendition of the magnetic domain structures in a ferromagnetic (blue) / antiferromagnetic (green) sandwich

The shown domain structures are those measured by PEEM for Co (blue) on NiO(100) (green). The in terface layer shown in brown is formed by interdiffusion and contains signatures of both the ferromagnetic and antiferromagnetic domains. It contains uncompensated spins and forms the link between the ferromagnetic and antiferromagnetic spin structures. A small fraction of the interfacial spins are pinned by anchoring in the antiferromagnet. These give rise to the pinning of the magnetization in the ferromagnet, i.e. the exchange bias phenomenon.

My present and future research topics are discussed in detail under Research Programs , Synchrotron Techniques and Highlights on the home page. Below I only give some pictures associated with these experiments.

The next picture below is an illustration of an innovative experiment conceived by Hans Christoph Siegmann. It explores ultrafast magnetic switching with the shortest and strongest field pulses available today. They are produced by a relativistic electr on bunch in the Stanford linear accelerator (LINAC) at SLAC. ( Nature 428, 831 (2004) ; Phys. Rev. Lett. 94, 197603 (2005) ). The caption explains the picture. More can be found under Research Programs and Highlights .

Artist's rendition of the ultrafa st magnetic switching experiment using the SLAC LINAC

Shown is a picture of the 2-mile-long linear accelerator at SLAC and superimposed as a black line is the path of an electron bunch traveling down the LINAC. The relativistic electron bunch is surrounded by a circular magnetic field as indicated by the red field lines. In the rest frame of the sample, shown in purple and located at the end of the LINAC, the electron bunch has a bunch length that can be changed from picoseconds down to less than 100 femtoseconds. When the beam traverses the uniformly magnetized sample, it writes a magnetic pattern into it whose shape and intensity distribution gives important information on the magnetization dynamics which follows the field excitation. Today, such experiments provide the shortest and strongest field pulses and have established a speed limit for the magnetic switching process. Since in computer data storage, magnetic bits are also switched by a magnetic field pulse, the SLAC experiment also shows the existence of a speed limit for writing magnetic bits in data storage. For more information, please see Highlights on the home page. The next picture illustrates the development of a new lensless magnetic technique. It utilizes Fourier transform holography to record a hologram from the sample and reconstruct the sample image by simple Fourier transformation of the hologram ( Nature 432, 885 (2004) ). More can be found under Research Programs and Highlights .

Illustration of lensless magnetic imaging

The x-ray beam from an undulator source with variable polarization is incident on a pinhole that redefines the source. The central part of the Fraunhofer pattern of the pinhole then il luminates a mask that consists of a ``sample hole" and a ``reference hole". The scanning electron microscopy (SEM) image on the lower left shows a close-up of the two holes which weredrilled into a Au film by a focused ion beam. In the shown case the mask and sample are integrated, as shown above the SEM image. The magnetic domain structure within the pinhole opening, recorded by a scanning transmission x-ray microscope (STXM) is shown on the right top. The experimentally recorded hologram of the sample by a CCD detector is shown in false color on the lower right.

One of the unique and most exciting capabilities of synchrotron radiation is the study of nanoscale structures on ultrafast timescales. My group has pioneered such time-dependent imaging experiments on nanoscale magnetic materials (Science 304, 420 (2004)) . We have used both PEEM microscopy and scanning transmission x-ray microscopy (STXM) at the Advanced Light Source.

In the figure below we show an example ( Phys. Rev.Lett. 96 , 217202 (2006) ). Using STXM we studied the time evolution of the magnetization of a 4 nm thick sensor layer (light blue), buried inside a nanopillar of 100 nm x 150 nm cross section. The time dependent images were taken as a function of delay time of the 70 ps long x-ray �probe� pulses relative to spin polarized current (�pump�) pulses injected into the layer. The current pulses of 200 ps rise time were generated by a pulse generator and wer e spin polarized by either transmission through (current flow from bottom to top in the shown pillar) or reflection from (current flow from top to bottom) a ferromagnetic polarizing layer (dark blue) in the pillar. As shown in the figure, we alternated 4 ns long positive and negative pulses to excite and reset the magnetization direction in the sensor layer. The images a) � i) were recorded at different delay times relative to the current pulse sequence, as indicated. They reveal that the magnetization in the sensor layer switches in a non-uniform fashion through creation of a magnetic vortex and its lateral shift. The magnetic C-state produced by the lateral shift of the vortex is metastable and may straighten out into a uniform magnetic state.

The switching process is initiated by the circular Oersted field which accompanies the charge current through the pillar and is then shifted by the exchange torque due to the spin current. The experiment clearly demonstrates the breakdown of the so-called macro-spin approximation which assumes that the magnetization is uniform across the nanoscale sensor layer and rotates as a whole during the switching process.

Much of the magnetism research described above is part of a book I have written with Hans Christoph Siegmann. Magnetism: From Fundamenta ls to Nanoscale Dynamics Series: Springer Series in Solid-State Sciences, Preliminary entry 180 Joachim St�hr and Hans Christoph Siegmann May 2006, Approx. 840 p. 400 illus., Hardcover ISBN: 3-540-30282-4 http://www.springer.com/sgw/cda/frontpage/0,11855,4-10100-72-100725344-0,00.html The book is a comprehensive treatment of dif ferent aspects of the broad field of magnetism. It covers historical aspects, fundamental aspects all the way to state-of-the-art problems and research in contemporary magnetism. It particularly distinguishes itself from other books on �magnetism� in its treatment of spin polarized electron physics, the discussion of spin polarized transport and the novel technique of x-ray dichroism for the study of magnetic materials. - Table of contents -

• Corpus ID: 30676514

SUMMARY OF RESEARCH ACCOMPLISHMENTS

• Published 2003
• Mathematics

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