how do you write a 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)

Explore other application documents:

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.