Applying to Grad School (Part 1): The Graduate School Application
First, a word of caution: this set of blog posts, intended to be a living one, is
only intended to be of use to those applying specifically to Ph.D. programs
in neuroscience; something I've learned in this process is that programs (even those
ostensibly similar in discipline) differ wildly in their expectations and
application processes. Caveat emptor.
This is the first in a series of posts on this graduate school application process and will go over my opinions of who should pursue a PhD, my application profile, and the parts of the application.
I also would greatly appreciate any comments or questions; you can shoot me a Twitter message @KenjiEricLee or an email at erickenjilee[at]gmail.com
Being back home in Hawaii, I've been afforded an indulgence that I so rarely (if ever)
have had over the past eight years: to just sit, to just think. On the white sands
of Kalama Beach (see banner photo), I took stock of the past year applying to
graduate schools: what went wrong, what went right, and about what I would
wish for others to know should the subject themselves to the same unsparing
referendum of one’s scientific self-worth. Although I wasn’t a better applicant
than others—mistakes were made that have since probably been overlearned
from—what follows next is hopefully still of some use to others.
I tried to think deeply about what I might offer given the already excellent
contributions to the "Getting into Neuroscience Grad School" literature from others like
Vael Gates, and
Oriol Pavón (each of whose
blogposts I found to be immensely helpful in my own application process).
I thought about what I could possibly add of value given that I've always been a
relatively poor student, went to an undergrad few have heard of, and hadn't met
an academic until college. But in this, I think, I might have some advice for
those that find themselves in a similar situation and still desire to attend
a good (even great) Ph.D. program in neuroscience.
This post will be
less prescriptive and more personal; it's meant to be an account of my
experiences, with as much honesty as possible.
But before I jump into my application experience, there was one very important question I (and you will have)
had to answer
Should You Even Go to Grad School?
Coming from a small liberal arts college, I always assumed that if you got your Ph.D., you could become a professor. I believed this largely because this is what was true
when my professors were going to school and there were no postdocs or grad students around to tell me otherwise; how wrong I was! It's important to first
get some facts about the odds regarding landing a tenure-tracked professorship.
Getting a tenured professorship is extremely difficult
"Life of the Mind!" they tell you as an undergraduate and what could be better than spending your days pushing back the boundaries of human knowledge?
What they don't tell you is that very few students
who enter a Ph.D. program become a tenured professor. It's very difficult to get any exactitude regarding how many students end up as faculty although
some have tried. Here's a thread from Penn professor Konrad Kording; although
this discussion is about "competitive" summer schools, there is some discussion about the rate that PhD's end up as TT professors at R1's.
The number that's thrown around for neuroscience currently is 7%.
If you make it to a competitive summer school (say with 50% acceptance rate), what do you think is the probability that you will end up being professor? I believe baseline of PhD-> prof=7%
But it seems like, if other fields are any indication, that these top schools are supplying the great majority
of faculty members. In fact, one study found that graduates from approximately the top 10% of institutions filled around half of all faculty positions; the top 20% filled 75% of the available positions; and the top 50% filled around 95% of positions.
On a personal note, this is why it was so important to me that I had alternatives should Academia no longer be an option. I made it a priority to get my masters degree in Applied Math which opens up the option of a career in data science.
Publish or perish is real
You must not only be very productive during the 5-7 years you are in grad school and 2-7 years you are a postdoc, you must also publish often and in the right journals.
Here are the funding and publication records of 61 new faculty in the life sciences who started labs at 21 large public R1 universities in 2018-2019. 36% have a first-author CNS paper, 75% have published in a CNS-family journal, and 16% have a K99. pic.twitter.com/IHsbn4UsJl
The top journals, called CNS (Cell, Nature, and Science), are disproportionately represented and most new faculty have published in the CNS-family. These results were also mirrored in a study here which finds that "whether or not a scientist becomes a PI is largely predictable by their publication record, even taking into account the first few years of publication".
My personal reasons for going to grad school
Knowing all this, I still ultimately decided to continue onto graduate school
for several reasons:
I feel most at home in lab: whether it was sitting at a two-photon for hours on end or programming late into the night, I loved doing it. Although I was paid hourly as a research associate, I would put in extra hours and weekends for the fun of it.
I actually got a talking to by my manager and told not to come in outside of work hours anymore because it could've been seen as "unapproved unpaid overtime" and expose the company to liability.
I love the community: Now there are some definite bad apple PI's in neuroscience but, taken as a whole, the community seems to me to be very supportive and engaged. There's something truly bracing about being participant in and contributor to
this global, multi-generational effort to understand the brain. I'm often struck by what's called an "oceanic feeling" seeing the tens of thousands of neuroscientists at SfN, finally meeting researchers whose work you've looked up to, or seeing lively debates about
the future of the field on Twitter.
Outcomes for my field are rather good: Even if the possibility of ending up as a professor are still rather poor, my field of computational neuroscience has had great success moving alternately into the fields of data science and
machine learning research. I've followed the paths of several grad students and postdocs over the last half-decade and many/most of them either become PI's or work as senior data scientists/ML researchers making very lucrative salaries (PhD's come in at the second level paygrade in FAANG's [L4/E4/SDEII]). Although this must be made
with the caveat that you can't just be in a "computational neuroscience" lab and expect this outcome, you must acquire the correct skills and publish in the right venues (NeuRIPS, ICML, Neural Computation, etc) along the way. This was a large reason why I took the time to get my masters in Applied Mathematics, software developer experience, and applied only to programs with strong computational programs. It also is convenient
that of all the fields of neuroscience, I most enjoy computational neuroscience and especially where it overlaps with theoretical machine learning.
What type of person I think should go to grad school
So it goes without saying that my opinion, as a first year, should be taken with a massive evaporated Mesozoic North American inland sea's sized grain of salt. But if you'll allow me to indulge, I think that a Ph.D. is a good idea for the type of person who desires a career leading a research team or conducting independent research; furthermore, they should not be ignorant of the outcomes for those in their field and able to
clearly assess the likelihood of their own success in said space. They should also be well aware of the opportunity costs of such an endeavor both monetarily and on a personal level. This is why I had/have no real qualms about taking several years off: it gave me time to reflect on what I wanted out of life and gave me a taste of life outside of Academia rather than being informed of what "real life" is through the Instagrams of non-academic friends. It was enough time
to see that a lot of the qualms students have about grad school as being conflated with the angsts of "Emerging Adulthood".
Now to get to the point, here's my application experience.
The Grad School Application
This section will go over the parts of the application and my personal application (all made available!);
There are three resources I've found to be tremendously helpful for this process but be warned, the last one on this list you click at your own risk: it sent my anxiety to 11 once I knew about it.
Reddit GradAdmissions: Some good advice here but also some really bad advice. A great place to start but make sure you're getting advice from users that
have actually been through the admissions process in your field. Here I got most of my information (some of it very wrong).
Twitter: If you haven't noticed by now, I absolutely adore Twitter as a tool for getting a pulse on what the neuroscience community is thinking. If you follow the right people, you will hear—straight from the horse's mouth—the
do's and don't's of applying to schools. Really a great tool for a more equitable applications process. Take a look at whom I follow if you're into computational neuroscience but I quite like @KordingLab, @neuroecology, and @analog_ashley as they frequently post (and stir up) insightful discussions often
apropos to applying to schools.
____Cafe: This site contains info going back a decade ago of who got in where and with what stats. There's also a useful forum to discuss with others the application process. Why did this site give me so much
anxiety? Well, it tends to attract only the most neurotic, high-achieving students that post (and sometimes lie) about their insanely good stats whining about how they don't know if they should apply to Harvard because they got a B in OChem even though they have a first-authorship in JNeuro, three glowing LoR's from BSD's, and have a 170 on GRE quant 🤮
Students will also update (usually within the hour) the Results page so you can see when interviews are being sent out. Good Lord I've probably hit refresh on that page several thousand times and there's no feeling worse than seeing your top choice appear to have sent out interviews while your unread inbox sits empty.
I know I'm sort of joking about it but I'm also sort of not. To get to this page, follow the instructions: enter "I consent to anxiety" and click here
My Application Profile
In 2015, I graduated from the University of Puget Sound with a double-major in math and biochemistry minoring in neuroscience. I also spent three years
in a neuroendocrinology lab exploring the estrogenic effects of bisphenol-A on zebrafish. Unfortunately, I also graduated with a 3.1 GPA and some C's
in relevant classes for neuroscience (curse you biochemistry like I even care about the pKa's of AA sidechains). I decided that it was pretty unlikely I'd get into any decent grad schools
so I decided to take some time off and for the last four years or so I was a research associate at the Allen Institute for Brain Science and also pursued my master's degree in applied math
at the University of Washington. I also took the GRE and did fairly well on it although not nearly as well as I suppose someone with an undergrad background should be expected to do. Perhaps it'll
be more fun instead to show my stats instead of prattling on. There are left and right arrows that are currently invisible; I haven't quite figured out how to make them a different color in Bootstrap.
If you're on mobile, you can swipe left and right.
Hopefully I made someone else out there feel better about having less than ideal grades! I've also provided my CV if you'd like to take a look
and if you'd like to use and reformat it for your own use, you can download it as a Word document here. I used some Google Fonts for the extra polished look;
I'm quite partial to Open Sans but Lato or Roboto are also good choices. I've also included a sample personal statement that you are free to download here.
Reading it again, it hurts to look at but hopefully it's of use to someone 😬 Here now I'll just jot down some thoughts on each. Succinctly, it is composed of (in what I believe is the order of importance):
Three letters of recommendation
Transcripts from all schools attended
CV (not the same as a resume)
A one to two page personal statement
GRE Scores (non-subject)
Possibly a diversity or research statement (but I won't comment since I never wrote one)
Letters of Recommendation
I didn't believe this at first but this is the most important part of your application. Why? I've seen applicants with pretty mediocre grades and research experiences get "this person walks on water" type letters of
recommendation from BSD's (an acronym for big names in the field) who were HHMI Investigators or NAS Members and it opened every door for them. This is the only part of the application that I've seen that can mitigate any other deficiencies
in any other part of your application; you can even ask your professor to specifically address these certain parts of your application if need be. Typically schools will ask for three letters but you can sometimes submit more; I
sort of got around that by actually having two scientists I worked with submit a joint letter. You'll want to ask your professors three months in advance and regularly check-up on them and you'll want as many as possible who've supervised you in
a research capacity. I had my manager, a former PI, and two scientists I've worked with submit letters.
Protip 1: Waive your rights to view your letter!. There is a box to check on every application whether or not you are waiving your right to view the letter of recommendation; always always waive it. The admissions committee can see whether or not you've waived your rights
and want to know that your professor is making an honest assessment of your abilities as a scientist without worrying what you might think. There's always a few students who don't know about this and absolute freak out on Reddit or GradCafe about it but there's not much they can
do other than email the committee saying they'd actually like to waive their rights.
Protip 2: PI's like letters from their friends: There I said it! Committee's look very favorably upon letters from other scientists who are friends and/or collaborators or else are from people whose work they respect. It can be claimed that this is a mechanism of insularity and it can also be claimed that
it is a good way to know how much to trust an LoR; I think both are true. I get the feeling that there are tons of great letters submitted to committees every year and only the recognized names are not "chaff". I've been told this by multiple PI's who served on admissions committees.
My undergrad transcript was pretty shitty to be honest. I thought (wrongly) that getting into grad schools was more about having difficult classes than high grades but by my senior year I realized I
had royally screwed myself over; I took two of the most difficult majors at my university and didn't have the study skills to manage taking 20 credit-hour semesters. In addition I was (after graduating) diagnosed with Delayed Sleep Phase Disorder
which had detracted from my ability to study (ironically as I write this at 3:00 a.m.). I did pretty poorly in core classes for both of my majors which I knew was going to count me out and so I made the expensive decision to also
try to pursue a master's in Applied Math which I did decently well in and had a 3.7 GPA after applying. In my opinion, you'll want at least around a 3.5 GPA to avoid the "danger zone" and make sure most of your core classes are A's with no C's.
Most of the applicants I interviewed with later seemed to have grades above this from what little I could infer. Looking back, I would have picked just the math major and double-minored and chosen classes that gave the appearance of difficulty
but perhaps had an easy teacher. I also would've been more upfront with having a diagnosed condition in my SoP; I had (and still have) trouble acknowledging its existence because it's largely unrecognized in the public.
Now I listed this as the second most important part of the application (to which I think many will disagree) but your GPA is probably the biggest filter metric that committees might use to disqualify you. For those with above a 3.5 GPA, they probably don't gain a ton
having grades higher than that and so the results are diminishing. For those (like me) who have below around a 3.2 GPA, this is a big red-flag and will raise serious misgivings within the committee as to your ability to conduct graduate work even if you have high grades
in a master's degree. This might be me obliging in post hoc ergo propter hoc but given how I did, I believe that my undergrad grades got me filtered out from many institutions regardless of my master's. One point I'll bring up again later but I very seriously underestimated how
competitive neuroscience Ph.D. programs are and of the schools I either interviewed at or had chatted with, it seems pretty typical that some get around 500 applicants for class sizes just north of ten individuals. Assuming that they get half of their students accepting offers,
that's an acceptance rate of below 5% 😱!!! I also seriously underestimated the utility of having the right connections. More on this later.
CV (Curriculum Vitae)
This document is not a resume, it is a scientific document meant to showcase your experiences and training. The jury is still out but personally I don't think that jobs should be listed that are irrelevant to your research like how you were a Subway Sandwich artist during the summers. Sure you probably learned a lot about working
with difficult people but space is limited to two-pages; surely there's more research-oriented experiences you could include right?
This section I'd probably tie with the Personal Statement as being the third most important part of your application because it really showcases your experiences and how that defines your "fit".
My CV has an unusually large number of publications but please don't think this is what you need before applying. In fact, I know of three individuals that got into every school (Harvard, MIT, Stanford, Princeton, etc) they applied to and none of them had any accepted publications. I truly don't believe that publications are a necessary
part of getting into a good graduate school despite what people think because it's so random as to whether or not your name gets on a paper or not. I will say though that having an accepted first authorship is a big deal and this I was told by a professor top R1 to be what their committee sees as one of the ways to stand-out at even
top schools. You might think that having an accepted first-authorship is an insane notion but remember that not everyone is a traditional student: some are coming from master's degrees or have worked in industry; further, some have had the privilege of work in labs throughout high-school and I know of at least one person with a first-authorship
out of high-school in eNeuro. I've also heard of someone that had two first-authorships in Cell before applying. I listed three of my publications as in review and two as in preparation but just know that although the former is acceptable at any career stage to have on a CV, the latter is not. It's okay when applying to grad schools but is considered a faux pas thereafter.
You can also include small details like awards including the dollar amount to give reviewers some notion of the magnitude of each and you can also list those grants you've submitted to or plan to especially the NSF-GRFP. Although award notices won't come out until after interviews, getting one can help you off of a waitlist. You should probably apply to this
grant concurrent with applying to schools but you'll get another shot (and only one now whereas before it was two) as a graduate student in either your first or second year. Also, you can't apply to this should you have completed more than twelve months of graduate school so if you've gotten a master's, you're ineligible (like me). You can find a list of
awarded proposals here. I also put down a short, one-sentence blurb about each of my publications and posters with my contributions to them as sometimes it can be hard for a reader to infer what role you actually played in them.
If you have the time, you may even customize each CV for each school by listing preferentially certain skills and details but for most people, they haven't done enough to fill two pages anyways so it's not like they can "pick and choose" what to list and that's fine. One other thing I've done to make my CV standout is to format it more attractively and to use color
and font to make it more pleasing to read. I used two columns, a sans serif (Open Sans) font, and color for each section header to direct the reader more easily to different sections. Having a link to a Github repo with complete and well-documented projects is a good idea as is a link to a website/blog.
The Personal Statement
My favorite part of the application! This is your chance to really shine as a budding scientist and to show the committee that you're more than just a set of numbers. Please, no cute stories. There was a huge Twitter furor directed at a certain PI (who shall be unnamed) who said something along the lines of "I swear if I have to read another application
starting with 'when I was 15, my father was diagnosed with . . .'." A lot of students and others were outraged that their very personal stories were so flippantly disregarded by a PI but the fact is that this type of personal statement is trite, overdone, and tells the reader nothing about who you are as a scientist. We all have our stories, and while important,
this is not the place to share them! The Personal Statement I used to apply to Boston University is available here but realize that this was for a program that admits directly to a lab. Let's break down how I wrote it and what I tried to convey.
Immediately I begin with a research statement indicating my interests that is at times both general and specific:
"I am interested in elucidating the cognitive mechanisms of the cortex that help link sensation to behavior"
You want to pique the reader's interest early and how they can place you into the grand scheme of the department. Don't bury the lede. I further elaborate
on this goal with a short description of anticipated methodologies and analysis techniques I'd like to employ and also a short bit about my end goal to be a professor. Please note that I was very specific here to demonstrate how closely my interests aligned with the of the PI I was trying to apply to work with.
Immediately after this, I parse my scientific path into bite-sized chunks, each lending a bit more insight into how my experiences have shaped my scientific approach and offer more detail into the roles I've played in my various research groups. You need to show and not tell! Like all forms of science communication (posters, papers, presentations, dissertations), you need to tell a story!
For my particular story, always returned to a certain theme which was the idea of a "virtuous loop": experiment feeds into theory which generates new testable predictions for experiment and so forth. Each stage in my story made clear to me this idea and I show my involvement in both ends of the loop. I also include a short statement at the end of each signaling that I understood the importance of each piece
of work; I understood that each contributed one small sentence to the scientific literature.
In the penultimate paragraph, I brought it back to the program and spent this time highlighting how I might fit in the lab of my desired advisor. For most programs, you'll have three (or four) rotations and thus will name the three or more PI's here that you'd like to work with along with one sentence for each about why you are interested in them. This may be used by committees such that they may give your
application to the correct faculty reviewers (which you've just named) to see if they are tacitly interested. I conclude with a short self-reflective paragraph and then add a signature which I think is a nice, personal touch.
Protip 1: Make sure the professors named are taking students, will still be at the institution, or haven't passed away! It's always super opaque as to the academic musical chairs that happens continually and your ability to see what's going on really depends on the strength of your network. Once again I'm going to hammer the point that Twitter is a godsend in this regard: what's the first thing a PI will do when they get the NoA (notice of award) for their R01
(and thus are likely looking to hire more students)? Tweet out the good news. You should also email them directly but that'll be talked about in another section. Also, when a PI moves institutions, they'll probably tweet that out too. One thing that I didn't know was how often PI's move around! As far as I'm aware, there are several forces that can engender this:
Spousal Hires: it seems to me that sometimes a spousal pair of scientists will join an institution even when only one is offered a position (the other may be a staff scientist of some sort) but this may mean that both will leave if another institution offers to hire them both as faculty. This actually happened at two institutions I applied to and I found out during the application process.
Tenure-related issues: being fairly naive coming from a SLAC (small liberal arts college) where almost everyone made tenure, I assumed this was also the case for most R1's but this isn't remotely true; some R1's have tenure-rates below 50%, pretty scary! This means that approaching years six through eight you can see PI's possibly moving around as either they think they'll have trouble making tenure and will thus start interviewing around or either they will have just been awarded tenure and will take that around as leverage to get hired "with tenure" at some other university. It's a grim calculus to make but take a look at said untenured faculty members record of getting funding, publishing in big venues, and graduating students and compare that to their peers at the same institution.
Sexual Harassment: Sometimes a university has come upon the knowledge that one of its faculty members is guilty of harassing other members of the department; instead of firing them outright, they will ask that faculty member to instead leave/resign. From the outside, this is hard to identify but will sometimes appear as an abrupt departure of a faculty member from one university to another (probably a much lower-ranked and less scrupulous institution). It
also is the case that sometimes faculty members will move institution, in protest, of their previous institution which continues to house known sexual harassers (or they themselves were harassed). It's an unfortunate reality of Academia that this still exists but I would be remiss not to bring it up.
You can also keep track of this by looking at which professors are giving talks at your university: sometimes (but not always) these talks are the public-facing portions of interviews. I knew of a couple professors that I worked with that were giving an unusual number of talks at universities recently and that affected how I ranked certain schools (because I thought the interviewing faculty member might leave). It's also pretty easy to tell if a particular professor has passed away as well (not uncommon) if you're on Twitter. The field is
very small so these sorts of events will resonate through the community quickly. I read one person's personal statement and had to inform them that they probably wouldn't be able to work with that particular professor.
Protip 2: Propose to them their next project and then they'll have to hire you! This is a piece of advice I heard in an interview with Professor Konrad Kording on MindCORE but if you provide a description of your research interests or potential projects on your personal statement, an excellent strategy is to anticipate what the PI's "next step" project would be. This is also great advice when/if you interview them! One way to do this is by reading their most recent papers (duh!) but another strategy I like is to read the public summaries of their ongoing grants. A popular way to look up grants is through NIH RePorter but I also really like the interface of Grantome. Another sly thing you can do (which I stumbled upon by accident) is to correspond with them via email and have them tell you themselves what they want to work on next; then meet them in-person and bring up the project again. Professors are busy people and they may not remember corresponding with you earlier about it. I did this once (again, by mistake!) and they were blown away. I don't condone this one I probably shouldn't have even shared it.
Protip 3: Visit the department's webpage and emphasize what they value: this is a tip from industry but every department prides themselves in some unique way according to certain values whether that's interdisciplinarity between certain departments, training in a certain regard related to a T32, or inferred through the subfields of their most recent hires. Departments will push for grad students that have training in what particular directions they are trying to move in or
to continue to buttress the strengths in which they've already achieved. I have a lot of training in computational approaches for latent space inference (manifolds!) and one of the best compliments I received was in-person from a professor who said, "you're exactly the type of student we're trying to recruit!" Awkward then that I didn't get an interview there 😓.
Protip 4: Find out where postdocs are getting hired and possibly name them as options: It can be pretty hard to tell but you should also consider adding new faculty to the list of professors you're interested in. You know almost certainly they are looking to attract students and also committees are inclined to help out their new members by admitting students whose interests align. I had some of the most engaging
conversations with these new faculty when I reached out over email and they seemed to be all enthusiastic and appreciative that I knew they had just gotten hired. One faculty member I chatted with helped single-handidly get me an interview for a program and also admitted because we connected so well (and he wanted a new student of course). But do beware the risks of working with new faculty: you can't know a priori how they will be as a PI and your careers in Academia will be inextricably entwined.
Okay well first of all, it seems that no one really cares anymore about this and yet I had to spend hundreds of dollars and dozens of hours studying for this I'm not bitter at all 😡. I even studied for the now defunct Biochem GRE at one point! So in the last year or so, it seems like
almost half of all schools have dropped the GRE as a requirement largely because it hasn't been seen to correlate strongly with performance in graduate school and also because it poses a not insignificant barrier financially speaking: several hundred dollars for materials, several hundred to take the test, and several hundred to send your scores out. Also,
it seems that some students are only applying to schools that don't require it and thus there's even more pressure on other schools to drop it lest they lose out on a significant fraction of the graduate students applying that year. You can find a comprehensive list for the biosciences here but realize
that it changes daily (Princeton Neuro just dropped theirs last w'eek). Anyways, I tried to do as well on this as possible to mitigate my grades and I thought I did an okay job but was very disappointed with my Quant section score as it's the most important for the sciences. Really not much more to say here other than that if you want to take it, I recommend Magoosh and following one of their guides (I did the Advanced 6-month). You can
buy subscriptions off students as well for cheap(er) off of the GRE subreddit. Really just aim for above an 80th percentile in all sections and above the 90th for quantitative if you want to do computational work but no huge biggie if you are somewhat below that. I've literally never seen a PI (on Twitter) say they care about the GRE except as a bar to hop over.
Some Thoughts and Acknowledgements
The Ph.D. application process is definitely a grind (and don't let some neurotic pre-med tell you otherwise)! It pays to start early and it also pays to apply intelligently: go where you know you're a good fit with professors willing to take you; have some insider knowledge of each school's reputation and dynamics; and also understand how each part of the application plays a role in your evaluation. It helps to have some compatriots to apply alongside with; for many, it's the other seniors at your university but since I was out of college, it was my coworkers at the Allen Institute. Specifically I'd like to acknowledge Becca de Frates, Maggie Chvilicek, and Rob Serafin for making the initial application process quite a bit more bearable! Also to Lucy Lai, Adriana Schoenhaut, and Chris Large for their materials and review of my essays. I know that it can be hard to reach out and ask for advice or for others' material so I've made them available throughout this post but I can also send more if you email me at erickenjilee[at]gmail.com. I'd also be more than happy to review your application as best I can.
Next up is Part Two of these blog posts which will go over my actual application experience and the timeline that I used! Not sure when it'll be up as this blog is mostly a way to procrastinate but seeing as I have a couple grant applications and abstract deadlines coming up, maybe soon! So stay tuned, smash that like button, and don't forget to hit subscribe!