Going to graduate school comes across your mind after finishing your bachelor’s degree. One looming factor that affects that decision is how to pay for it. If you want a master’s degree, you will probably pay for it out of pocket. Universities are not going to cover it because you are there for two years, learn an excellent set of skills, and then you leave. Thus, there is no incentive for them to support you. Many companies will cover master’s degrees, but this support typically comes with an obligation such as working for them a certain amount of years after completing your degree.
When I was finishing my undergrad, I was fortunate enough to receive Sandia National Laboratory's Critical Skills Master Program and Master’s Fellow Program. These fellowships cover tuition, stipend, and tuition-related costs at any university of your choosing, pending acceptance. During summer breaks from the master’s program, fellows have a paid internship at Sandia. Once a fellow completes their degree, for every month she/he was in school, she/he would be obligated to work two months for Sandia. Thus, if you went to school for two years, you would owe about four years before being free to leave Sandia. Pondering this, I declined their fellowship offer because if I took it I felt that I would get comfortable with the money, and the break would be too long for me to go back for my Ph.D. I am now a fourth-year Ph.D. student, and I have never regretted my decision.
As a Ph.D. student, funding options are different. If you are going for a STEM Ph.D., there is a high probability that your advisor/PI will fund your Ph.D. from her/his grants. You may ask, if I have a stipend and my tuition paid for, why would I want to apply for fellowships?
The first reason is that the professor that you want to work with has limited funding. Assuming that she/he is well known in her/his field, then multiple students want to work for that professor. Imagine a scenario where the professor has funding for four students, yet there are seven that want to work for her/him. There are going to be three students that won’t have that opportunity. If you come with an external fellowship that changes the situation as the fellowship reduces the financial burden on the professor (some fellowships cover more than others, not all provide the same stipend and/or tuition expenses).
A fellowship can provide you the freedom to work on a research area of your choosing. Your advisor/PI sends grant proposals, and if the grant is awarded to your advisor, then she/he needs a student to provide results on that grant. Depending on the grant and what was expected, it may not be the area of research that you are motivated by.
Another reason to apply for fellowships is that some provide a greater stipend than what the department is offering, and some may offer a summer internship. Having that internship can help if you want to work for that company. For instance, there is the Facebook Fellowship that offers a 37K stipend, a 1K allowance to be used for a conference, and an optional summer internship.
Fellowships can open the door to great opportunities and when applying do your due diligence because for some of these fellowships you may only have one or two times to be eligible. When applying, be mindful of completeness, conciseness, and coherence. Make sure you submit everything including the additional materials such as letters of recommendation. That is critical because I have seen people spend several hours on their application only to become disqualified because the letters of recommendation were not submitted by the deadline. Give the people writing on your behalf a good amount of time to write the letter. Send nice reminders about the deadline, especially if they are professors.
Omit needless words. The reviewer is going to spend minutes on your application, and you want to make sure it is to the point and clear for the reviewer to understand. Have close friends or professors read your essays to see if the point you are writing about is met. If multiple people get a different message than what you meant, it is a sign that you need to work on it.
Make sure that the application materials blend with your essays. For example, say in one of your essays you write about an internship experience that was the cornerstone of you wanting to go to grad school and work in that research area. If you do not provide a letter of recommendation from that experience, it may seem odd. For the reviewer, he/she may want the other piece of the puzzle from that experience. It would be similar to watching a movie with plot holes, and in the end, you want your application to be a movie such as The Godfather and not Sharknado.
An additional tip is to look at how the fellowship evaluates an applicant. Not all the fellowships have the same rubric. In my experience, I looked online for how National Science Foundation Graduate Fellowship Research Program (NSF GRFP) and National Defense and Science Engineering Graduate Fellowship (NDSEG) evaluate a potential fellow. NSF GRFP weighs research experiences more than NDSEG, while NDSEG weighs GPA more than NSF GRFP. Also, when asking for letters of recommendation, make sure that the person writing it will write a strong letter of recommendation. If the letter of recommendation is weak, it will decrease your probability of getting the fellowship. Try to stand out from the crowd, because these reviewers will get numerous applications.
One of my experiences was with the Ford Foundation Pre-Doctoral Fellowship. In one of the essays, it asked how you are going to help underrepresented minority students. After the deadline, I asked multiple friends who applied, and they all said that if the students of interest had enthusiasm in their field, they would mentor them. For me, I thought other people would say that, and in my essay, I said that I would work on multiple workshops to help these students gain a diverse set of skills. I know people may not be enthusiastic about machine learning like I am, but there are still abilities that they can learn. The workshops I had described were about programming, 3D printing/CAD, and many more topics as well, because some of those students will get a different engineering degree, so they’ll need to learn a broad set of skills to have a good foundation. As a reviewer reading this compared to the other applicants, which one would you choose?
CJ Barberan is a fourth-year Ph.D. student whose advisor is Rich Baraniuk. His research focuses on deep reinforcement learning with applications in computer vision. He is a GEM, NSF, and NDSEG Fellow. He is happy to share his essays from NSF GRFP, NDSEG, and/or, Ford Foundation Pre-Doctoral. Please email him at firstname.lastname@example.org.