For context: I'm a 1st-year PhD student at the Annenberg School for Communication at the University of Southern California. I study how automated technologies like generative AI are transforming cultural and creative work. During the 2022-2023 cycle, I applied for and was awarded the National Science Foundation's Graduate Research Fellowship, often abbreviated as the NSF GRFP, under the category of "Social Sciences - Artificial Intelligence."

PhD fellowship applications are rather nebulous and difficult to navigate. When applying for the NSF GRFP, I strongly benefited from the online resources shared by previous awardees, such as a compilation of application materials from past awardees, Alex Lang's website, and Mallory P. Ladd's website.

Nonetheless, I found a lack of publicly available tips on how to craft a strong application for someone who pursues the critical studies of technologies across disciplinary boundaries. The research I proposed to the NSF is interdisciplinary by nature; I drew on traditions, approaches, and frameworks from Sociology, Computer Science, Science and Technology Studies, Communication, and Human-Computer-Interaction. My  application being successful is a testimony that NSF does fund research in this space, and I want to reflect on my experience to highlight what worked (and what didn't).

Most of the content below are general tips that are applicable to all NSF GRFP applicants, but there're also pieces of advice that I would specifically like to share with people who are navigating the interdisciplinary space of the critical studies of technologies. While I only applied for the NSF GRFP, I imagine the tips I shared I below to also be (somewhat) applicable to other PhD fellowships, such as the Ford Foundation Fellowship, and the Microsoft PhD Research Fellowship, to name a few.
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Personally, I applied for the NSF GRFP for a few reasons:

The NSF GRFP was created to broaden participation in science and engineering of underrepresented groups in the United States. The five-year fellowship provides three years of financial support inclusive of an annual stipend of $37,000 with a $12,000 cost of education allowance. The NSF GRFP is highly sought after as a tremendous source of financial support for graduate research.

As a general rule of thumb, to be eligible for the NSF GRFP, you must be (1) a US citizen, US national, or permanent resident, (2) intend to or is pursuing a research-based Master’s or Ph.D. program at an accredited U.S. institution, and (3) have not completed more than one year of graduate study. (There are other criteria to consider, so make sure to run the eligibility questionnaire to double check!)

The NSF GRFP runs on an annual application cycle. Each year, applications are due around mid October (with reference letters due by late October), and the results will be announced in early April. Each person can apply for a maximum of two times. Once before you start graduate school, and another time during the first or second year of graduate school.

Initially, I was a bit hesitant to apply for the NSF GRFP as part of my PhD application cycle. I felt that I had not yet developed a fleshed out research agenda that I could confidently articulate. Nonetheless, I was strongly encouraged by peers and mentors to still apply and see how it goes. In retrospect, I'm glad I took their advice – I immensely benefited from the process of putting together my application materials for the NSF GRFP. I was able to recycle a significant portion of the writing I did for the NSF GRFP for my PhD applications.

I couldn't stress this enough, but I strongly encourage everyone to start (actually) writing your application as early as possible! I held off on writing my materials until I had a pretty clear sense of what research agenda I'd be proposing in my application. While I was able to finish a submission-ready full draft by late September, I had little time left to share my materials with others for feedback and to iterate on my application.

‍In hindsight, I wish I spent less time on worrying about what concrete projects to propose (e.g., studying how media professionals use AI-powered writing assistants in their everyday work) and focus on jotting down the underlying questions that motivated me to pursue a PhD in the first place (e.g., how AI is transforming cultural and knowledge production).

Yes, the writing process for a major fellowship like the NSF GRFP can indeed be daunting (at least it was for me when I applied!), but it's important to keep doing the work than worrying about not doing good enough work. Notably, you're not married to the research you proposed in your application, so don't be afraid to propose the bold ideas you have at the moment for fear that you may not stick to it throughout your PhD.

Each application includes two statements:

In addition, each application comes with 2-3 reference letters. These letters are where your mentors can elaborate on aspects of your personality/achievement that didn’t fit into your statements. As such, think carefully about how different people can speak about your different aspects of your strengths. In my case, my 3 letters came from my honors thesis advisor, the PI of my undergrad lab, and my internship mentor, who can speak about their experience working with me in different capacities.

To be very honest, I don't exactly know what made my application a successful one. Nonetheless, I thought it would helpful to share aspects of my applications (1) that I paid particular attention to when crafting my materials, or (2) that the reviewers positively highlighted. Below are some tips that I would like to highlight drawing from my experience:

Each year, the NSF publishes an official solicitation for the GRFP. Please take this document very, very seriously. This is the upmost important piece of information that you should reference multiple times throughout the application process. It explains (1) formatting requirements that you should follow to make your application eligible for review, (2) the criteria by which your application will be evaluated, and (3) emphasis area that the NSF is prioritizing in a given year.

Even though you may feel that you have a good sense of what the NSF is looking for after reading the plethora of tips and advice shared by past awardees, please make sure to read the latest program solicitation so that you're aware of changes to the (1) formatting requirements and (2) priority areas. I only found out that artificial intelligence is a high priority area by reading the document very closely, and this insight gave me a better perspective that informed my strategic choice of my field of study.

Overall, the NSF is looking for two things in your application -- (1) Intellectual Merit and (2) Broader Impacts:

It's very important to keep the two criteria in mind when drafting your application materials. Both statements (the personal and the research) must address both criteria (intellectual merit and broader impacts), and these must be explicitly and individually addressed under separate headings. In my experience, I often found myself emphasizing one but not the other at different stages of the writing process, and I had to re-balance my content to make sure I clearly address both criteria in a balanced structure.

Your NSF application should serve the purpose of convincing reviewers that you are positioned to be a future leader in your field. Thus, before you delve into the writing process, it's important to consider who your reviewers might be and how they might view your application.

As part of the application process, all applicants were given an explicit opportunity to suggest what kind of reviewers they would prefer -- you can indicate (1) a Major Field of Study and (2) a Field of Study. For instance, "Human Computer Interaction" is a Field under "Computer and Information Sciences & Engineering," and "Communications" is a Field under "Social Sciences."

This is, in my opinion, the trickiest part if you're pursuing research with an interdisciplinary flavor. While the NSF explicitly encourages interdisciplinary research, the reviewer allocation process is nonetheless organized along disciplinary boundaries. As the NSF stated:

"Applications are reviewed in broad areas of related disciplines based on the selection of a Field of Study. Selection of a Major Field of Study determines the broad disciplinary expertise of the reviewers."

As such, it's important to articulate your research in a language that is legible not only to your subfield but to your adjacent fields as well. Knowing this, it's important to explain rather than assuming the reviewers are familiar with the specific intellectual backdrop on which you're articulating your research vision. For instance, in my proposal, I didn't just assume the social scientists reviewing my application are familiar with the mechanisms of generative AI; instead, I explicitly outlined such mechanisms in ways that are sufficient for them to understand how and why the adoption of such technologies might complicate cultural and creative work.

For those whose research doesn't fall squarely along disciplinary lines, you have to quite strategic with the Major Field and Field you indicate in your application. Here' are 3 routes I'd suggest that you consider (that I personally ruminated over in my own process):‍

Be as specific as you can in outlining how you plan to execute your proposed research. This is an area that I could've done better. In my application, I proposed to collaborate with industry practitioners for organizational ethnography, I did not articulate how I plan to access and build rapport with these stakeholders. My reviewers explicitly highlighted this as an area of improvement, and I hope my experience can shed some light on the reviewers' emphasis on practicality.

In addition, I also highly encouraged everyone to articulate how you plan to utilize the resources at a specific department or institution. In my application material, I explicitly mentioned the institution and department where I might potentially pursue my graduate research. Beyond simply listing the PhD program, I highlighted how I planned to utilize the resources there and how the place is uniquely positioned to support the research I proposed. I also sketched out out what centers and people I considered collaborating with and how they would help me advance my research goals.

This strategy worked in my favor; several of my reviewers wrote in a positive light that I would have the adequate resources and support to pursue my proposed research at the program I listed. To quote one of my reviewers' words:
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"The applicant is pursuing an institution and a geography for graduate study that, while certainly not the only possibility for advanced study in the social science of technology, offers ample, well-aligned resources and support."

The same logic applies to those who are applying to the GRFP as 1st or 2nd year graduate students. It's important to convince your reviewers that you're well-positioned to carry out the research you propose, and it's important to explicitly articulate this rather than assuming the reviewers can tell from your track record.

If you didn't get the fellowship, It's ok to feel disappointed after putting in the hard work on your application,. Nonetheless, one should know that only around 15% of the applicants are awarded the GRFP each year, and there're a lot of factors that are beyond the applicants' control on an individual level (e.g., bias against candidates outside of the circle of elite institutions).

On the other hand, it's important to know that your hard work isn't in vain! The application process for the NSF GRFP is a valuable experience learning how to articulate your research to funding agencies, and this is something you'll continue to do for the rest of your research career. Take what's valuable from the reviews and keep up the good work :)

If you got the GRFP, CONGRATULATIONS!!! It's a major achievement and you should take some time to celebrate what you've accomplished! Other than celebrating, there are some logistical and practical considerations that you should think about if you're an incoming PhD student:

Yes! Please get in touch. I'm more than happy to answer any questions you may have. I'm also happy to share my application materials with you if you're  coming from marginalized backgrounds (BIPOC, first-gen, low-income, with disabilities, etc.). Just make sure you don’t circulate or plagiarize them, and I do consider doing something similar in the future to make the research world less opaque and exclusionary.