Last month, I served as one of the PhD application evaluators for my village’s local graduate school (IMPRS), and I took some notes while reading through the applications on what I looked for, in real time. It’s probably a bit late for this year’s application cycle to be immediately helpful, but I figured it’s already written so why not share them, so I fleshed it out a bit into a full post.

I had helped screen late-stage candidates a few times before, like giving internal evaluations for the handful of people being considered for our lab, etc., but this was the first time I formally served as an at-scale pre-screening evaluator, i.e., reading large batches of generic applications targeting the graduate program. This a very different thing, and it was an interesting process to slowly realize which qualities in the package I was looking for—explicitly and implicitly—and therefore what made a great PhD candidate in my mind (right or wrong).

There’s a good chance that I get canceled for a) spilling our ivory tower secrets, and/or b) being unreasonable one way or another in the evaluation process. Still, I’d be happy to hear thoughts about any of this: I’m curious to see how this fits with other people’s experiences in general, and especially if you find some part of this unreasonable / unfair / unrealistic.

TL;DR? I think the most useful takeaway from all this, aside from the specific advice about the components, is to put yourself in the shoes of the evaluator and optimize your application to make their life easier. This is not the interview: this is the stage before the interview, and has a different set of things one should optimize for—namely, to get to the interview.

Brief context on graduate school applications and intercontinental differences

About the specific situation: the IMPRS graduate program accepts PhD students from all over the world into Uni Tuebingen, Stuttgart, and their adjacent MPIs, and I think it gets a couple hundred applications targeting the program itself, not a specific advisor. This big batch was split between lots of evaluators, and each application was assessed by 2-3 people, so I had about 20 or so to look through and give a grade between A to C. This was the first stage of the process, and the applications that successfully passed this prescreening stage (A-B grade across the evaluators) move on to be evaluated by their potential PhD advisors, and contacted for phone / video interviews. It was similar for UCSD Neuroscience as far as I recall, which was another big program that gets a lot of applications, and I think there the current PhD students actually help in evaluating, while UCSD CogSci doesn’t have this big pre-screen stage that was outsourced to people other than the faculties themselves. What’s also pretty universal are the components of the application package: motivation / personal statement, CV, transcript, standardized test scores, and recommendation letters.

Some key differences that’s specific to the geography: being a European program, most of the candidates I evaluated here have already completed, or are on their way to completing a Master’s degree, in comparison to the direct-to-PhD route from Bachelor’s that’s more common in the U.S. So this changes what would be reasonable for an evaluator to expect, e.g., Master’s student already with conference presentations or even papers, though this also depends strongly on the field (biological neuroscience vs. machine learning). Also, PhD positions in Germany (and most of Europe?) are actually not usually affiliated with a “graduate program”, and are often advertised (more or less) like a regular job post. So it’s totally possible to have accepted a PhD offer with one of the faculty members affiliated with IMPRS, but not be accepted into the program. This is not usually possible in North America, as you’d almost always start a PhD as a part of the graduate school of a university, and begin with your cohort in September. This creates a sort of strange scenario in the case of European “graduate schools”, and certainly in this particular situation, where some applicants have already started their PhD with an affiliated advisor, while other “external” applicants are applying blind to compete for “real” spots in the graduate school. Although, this also implicitly happens a lot in the U.S., where a current lab tech or research assistant applies formally to continue with the same lab for their PhD, and if the advisor agrees, then the rest of the application process is pretty much a done deal (unless they really bomb the interview for whatever reason). In any case, this post is about getting through the batch pre-screening process of a graduate school, and is therefore, strangely enough, more applicable to the average North American PhD application than a European one.

“Summary”: consider your target audience & general strategies

One note to put you in the shoes of the evaluator (me!), and probably the most helpful: I think for most people doing app reviews, they don’t consider this a part of their real job aka research, but obviously still want to (I hope) do a good and fair job since it tangibly impacts a student’s academic future, especially if they are from a situation or country where good opportunities like these are rarer. This probably means reading through applications on the weekend or at night, in between real life, so the cost function is very much weighed by a personal time constraint, and if one is assigned only 20 applications (out of, say, 300), that’s about 3 hours at 10 minutes per application. Practically, this translates to “make a good decision as quickly as possible”, and not “be absolutely certain that the decision was the right one”. I don’t think this is necessarily “optimal”, but it’s the way it is, and multiple evaluators are there to mitigate randomness in the process.

Given this, there is a very complicated decision-making sequence in my head, a lot of that having to do with an internal evaluation of whether a thought was a correct “first impression”, or an implicit and systematic bias (an aside: kudos to the coordinators for requiring the evaluators to watch these videos on implicit bias - my biases definitely don’t get fixed with a 15-min video, but at least it primes me for this train of thought). To explain this in a much nerdier way, it’s like a drift-diffusion process where I’m shooting for one of the two boundaries: clear accept (A) or clear reject (C), and if I’ve read through the whole thing without a clear opinion, it’s a maybe (~B). I think in reality, I actually had a drift bias towards the positive boundary, meaning I’m usually moving through one component of the application package after another looking for evidence that would support a positive decision, and the final evaluation is “how long did it take for me to reach a robust positive evaluation?”

What does this mean for you, the applicant? Present information that would bias a strong positive decision as quickly and concisely as possible, and clearly motivate (i.e. explain away) why factors or potential red flags that would induce a strong negative decision should be disregarded. Remember that you are one of 300 people applying, and that, more importantly, you can’t change your grades or publication record in the week that you put together your application package, so all that stuff is set in stone. Just work with what you have, and make it very easy for the evaluator to reach a positive decision, i.e., within the first couple of paragraphs of your personal statement. I’m sure this logic applies in many scenarios where pre-screening at mass happens, i.e., HR at Google going through resumes or whatever. If you know what the evaluator’s cost functions are, then it’s simple to target those directly, but that’s often a very black-box decision process, and even more frequently just implicit and idiosyncratic, so candidates often run into the risk of barfing out everything they have to say about themselves and thereby putting emphasis on nothing.

So, part of what I want to do here is to make those targets explicit for those not privy to the ivory tower word-of-mouth wisdom, at the risk of divulging the potential fact that I’m actually a huge racist and elitist bigot or something. Finally, in my opinion, it’s much better to present yourself concisely and accurately, and risk a rejection due to a lack of mutual fit (and try to not take it too personally), than to be vague and broad to get an acceptance only to later find out that it’s not a good fit.

All that being said, the rest is organized as such: 0) qualities of a capable PhD applicant I’m looking for (to confirm) in the components of the application, and then, in order of priority (for me), they are: 1) recommendation letters, 2) personal statement / CV, 3) grades and standardized test scores. They are ordered this way because a recommendation has a high upside potential, but is at worst neutral if it’s not the most enthusiastic reference (very few people will straight up say this person is incompetent). Compared to the grades, which has low upside potential because mostly everyone applying for grad school has good enough grades, and could potentially tank you if you had really bad grades, but if someone didn’t get good letters, then at least really good grades will earn them a consideration. Pretty sure that’s how I got into grad school in the end.

Again, I feel like I have to repeatedly state this caveat, which is that all of this is very idiosyncratic, and I’m really not even sure how differently different people treat this process, so take it with a bucket of salt before you apply any of the “advice” here. The one applicable meta-advice is probably to scope out what people at the program you’re applying to are roughly looking for (just like any other cover letter you write in an application).

0. Qualities of a PhD-ready candidate

I’m a year out of my own PhD, wtf do I know about picking good PhD students? Probably not much, to be honest. At the same time, I’m the schmuck reading your application, and two thirds of the other evaluators are schmucks just like me (postdocs or even senior PhD students), so this is what you have to work with—welcome to a supply-rich labor market. I’m not saying these are the qualities that will necessarily enable a successful and timely PhD—many things outside of your control can often play a stronger role—and obviously much of this is idiosyncratic to me and my personal experience, as well as those of my friends and students I’ve worked with, and just as importantly, is a function of my (somewhat cynical) view of academia. To really flesh this out, it will take a whole other blog post (that I plan to write), but for the time being and considering the huge caveats I just mentioned, these are some qualities I looked for in the applications / candidates, and I’m very curious if these are completely off the mark. It also has to be taken into account that, when I started my PhD, I don’t feel like I could have demonstrably proven any of these qualities in myself, certainly not by my research output during my Bachelor’s degree. But that’s more just a generic comment about evaluations: there will be false negatives no matter how tight your criteria are, because an evaluation of the present sometimes has no correlation with the future, and I’m thankful somebody took a risk on me.

So, here’s the list, with little to no explanation because that’s for another day. Note that these are mostly “traits” that are harder to teach, compared to, say, linear algebra or programming:

  • perseverance (self-explanatory)
  • ability to work independently, and alone (again, self-explanatory)
  • resourcefulness in learning (how to use Google)
  • ability to work (or at least co-exist) with other people
  • critical thinking and maturity in acknowledging limits
  • interest / passion (in pretty much anything)
  • integrity and responsibility (especially when you fuck up)

There are some other important qualities to consider, but clear contradicting evidence in any of these above traits would be a red flag for me. Again, I am in no way claiming these are “the traits” one must have, this is just my list, and every one of the evaluators has one (implicitly or explicitly).

1. Recommendation letters

One liner: make sure the people that are writing letters for you are dependable and will at least make an effort in demonstrating that they personally know you - better to ask someone that know you well (but is a little less famous or further along in their career) than a big shot who will generically describe you like a number in a classroom.

Not really a good sign that the first thing I look at is the thing where, for the most part, the applicant has no active role in shaping in the short term. But this, by and large, is for me the fastest way to confirm that a person is ready to start a PhD. Basically, if someone that you’ve worked with and has a PhD themselves says that you have shown evidence of being ready for PhD-level research, that’s about as good as it gets. Best case scenario, I read through the two or three letters and smash that A-grade as long as there are no obvious and unexplained red flags in your personal statement or grades (like addressing the wrong graduate school or a B in statistics while applying to do a machine learning PhD). Then I’m pretty happy because we can quickly move on to the next application. But most of the other cases require a more detailed consideration of the components in the following sections, and for the recommendation letter, my work is trying to parse whether your recommender:

a) is a British or German academic and therefore scale their relative evaluation of you based on the emotional range they consider appropriate to communicate in a professional setting (this is not entirely a joke),

b) doesn’t quite know how to communicate why you are a good candidate but is nevertheless excited to have worked with you (this is rare for professional academics often writing recommendation letters, but possible for junior people),

c) is subtly trying to signal their reluctance, or is just flat out unexcited / unimpressed, or

d) don’t actually know who you are (extremely obvious).

Here’s the one concrete advice I can give on this topic: pick very wisely who you ask to write these letters for you. You want somebody to be able to say something of substance about you, that they have concrete experiences working with you in a research setting, and that they are confident this will carry forward into your next stage of life. Particularly convincing are the ones that say “I wish the candidate had stayed in my own lab for their PhD…”. Again, if they spell out in their letter all the qualities that I am looking for in section 0, and justify statements about some or all of those qualities with concrete examples of your interactions, then that’s about as good as it gets for me. One potential issue here is that some letter writers don’t necessarily know how to write convincing letters that follow the claim-evidence structure, but then you’d at least hope they will convey some positive emotions about you, and reiterate claims you would make about yourself. If in doubt, send them this blog post (no, don’t really, that would be a bit…patronizing).

I think the above is pretty obvious, the question is, what do you do when no such person comes to mind for you? In my opinion, what’s worse than an unskilled writer or perhaps a lowly postdoc or PhD student writing your letter is the full professor who really has no idea who the hell you are. Obviously, if you manage to get a convincing letter from Terry Sejnowski or Eve Marder or whoever, saying you were a superb student in their seminar / research project course, then that’s optimal (and frankly you can stop reading at this point). Personally, I think it’s much more valuable to have a full and positive portrait of a candidate from an unknown person than a lukewarm description saying “this student placed in the top 5% grade-wise in my course, and was generally prepared, helpful, and on time” signed by a well-known person because I can obviously read off that information for myself in your transcript, so it doesn’t add much. Hell, if you really have no one in a research setting to write this letter for you, I would rather see a letter from a long-term coach or work supervisor that can explicit spell out those PhD-ready qualities. But again, this might just be me.

On the flip side, you do have some influence on what their portrayal of you looks like, by reminding or informing the person of who you are: you might provide a lot more supporting information to help them help you, or maybe even ask if this more well-known person can write you a good letter. I’ve heard that some people explicitly tell candidates to ask someone else when they won’t be able to say anything substantive, which sounds like a slap in the face, but it’s really doing both people a favor. But it’s a tricky situation to navigate as a student because you might think it’s offensive to ask and unask somebody. So push comes to shove, I’d say just ask someone who you have a concrete personal relationship with, and let them know early enough so they can prepare. Even more helpful is to outline the arguments for them, i.e., “I am resourceful because when our team bus broke down, I managed to get us to the game on time because X/Y/Z…” Though you want to be careful here that they don’t copy something exactly as you’ve worded it in your application, because then it could look like you wrote your own letter for them to sign off. This happens often enough and to be honest, I don’t consider this a “red flag”, per se, but it’s just another sign that they don’t know (or care about) you as much as they should, and so it doesn’t really serve as a piece of positive evidence.

A more general rant about recommendations and letters: first of all, the percentage ratings in the form of “this candidate is among top 5%/10%/20% of students I’ve worked with” is often quite unhelpful, unless the prompt very specifically states the pool they should be comparing to, or even what that denominator actually is. An average professor in the U.S. teaches 3-4 classes a year, of maybe about 50 students, which is 200 students every year. On the flip side, they might see 5 new research assistants in their lab per year, tops. So “top 5% of students I’ve interacted with” is very different depending on what their interpretation of “interaction” is. I don’t really take this into account anymore when there is a letter attached, and find it hilarious when someone writes a very strong positive recommendation but put down “top 20%” or something.

But the bigger point is this: as long as we’re still using recommendation letters as a part of the evaluation process, let’s not kid ourselves in how “objective” or fair we can be in academia—it’s inherently based on word-of-mouth recommendations, like your local pizza joint. I’m not saying they’re not useful, like I just outlined above, they are extremely useful for an evaluator to make a judgement—but under the current system and at a lack of a better way for the candidate to demonstrate their qualities themselves. This means the person writing the recommendation has a huge say in how they want to portray the candidate, and again, also very much depends on how well-known they are and how skilled they are at writing these letters. I don’t know if this is something you get taught in professor school, but it’d be quite unfortunate for the poor student who asks a professor that just doesn’t really use nice words in a letter. Conversely, the ones that figure out that modern academia—like every other human enterprise—is first and foremost a social construct, and therefore can expedite their own success by placing their mentees into positions to succeed, such as a very competitive graduate program, are the ones that accrue more resources and more opportunities to further the propagation of their ideas in the long term—good or bad. It might be cynical, but it’s not untrue.

2. Personal statement and CV

Next, the personal statement and your CV/resume offer very different information, but they are similar in that these are the components over which you have the most control when preparing the application—not necessarily the objective content, but in how you present that information. Basically, it should convey who you are, why you are ready to do research, and why here, in as few words as possible.

First of all, if you have multiple publications or conference papers at well-known venues, then I don’t necessarily care about who you say you are (unless, again, there are red flags about your ability to coexist with other people). I still look at the recommendation letter first, though, because the tangible achievements are almost always mentioned in the letter anyway (assuming you asked a supervisor / co-author to write), with the additional upside that they might positively comment on you as a person in ways that’s not apparent through the publications. The real question is: what should the majority of the applicants—those without demonstrable proof of previous research success—do? Pretty simple: make my life as the evaluator easier. Specifically, that means think about the arguments you want to make (re: the qualities), structure your statement and CV to deliver this claim and the evidence as quickly and concisely as possible, and don’t have any major fuck-ups.

Let’s address that last point first because it’s the easiest. A major fuck-up means, for example, uploading a statement addressing a different school or program. Honest mistakes happen, and there is no situation where somebody intentionally uploads a wrong letter, obviously. But what this conveys is a lack of interest, even though we all understand that any given candidate could be applying to 5-20 different schools, at the very least, especially in the North American system come November. This could also reflect a lack of care and organization, but in the end, I’m not sure if this is an objective red flag as much as it is an offence to the evaluator’s ego, like “damn you couldn’t be bothered to at least check it again? I guess we aren’t so special here to you,” which is hilarious because I couldn’t give less of a shit personally whether a candidate ends up in Tübingen or Böblingen or some other small European city with a good graduate program.

But a related and much more realistic scenario is that the statement is so completely generic that it could have been used for any program in the world, which would fail to convey why this place is the “right fit” for you. This means a lack of awareness about the research areas of the PhD supervisors, no actual mention of supervisors you are interested in working with, or just flat-out saying incorrect things. Again, this doesn’t necessarily mean you would be a bad PhD candidate, but it doesn’t really make me excited about having you in the community here. The ego joke aside, a tailored statement could convey a strong fit and possibility for collaborations with people around you, if not in a concrete project then at least being intellectually enriching for all parties involved. Sure, some applications are throw-aways or for “safety schools”, but if every school you apply to thinks that they’re your safety school, then you’re probably gonna have a bad time, nevermind wasting a bunch of money on the applications. Practically, the most reasonable thing is to have a free paragraph or two at the end of your statement that can be exchanged in a program-dependent manner. At least go through the effort of Googling some names. Again, this is not just to stroke someone’s ego, it’s for everyone’s benefit that you arrive into a graduate program with some indication that it would be a good fit, and on the off chance it doesn’t work out with your first supervisor, at least there’s some chance that you find another lab working on topics that you’re interested in. If your statement can convey this adequately, it’s a really big plus for me. This seems pretty obvious once you know it, but lots of people, especially those that don’t have a “mentor” in academia, don’t know. I certainly didn’t do this when I applied, that’s how I ended up getting a PhD in Cognitive Science, so it’s not the end of the world, evidently.

Extending that last point but transitioning to the topic of “who you are”: a clear and accurate description of the advisors you are interested in not only demonstrates your research interests, but your academic maturity. This is honestly pretty rare to see in PhD application statements just because people won’t have had that much experience to delve deeply into a topic, but when I see some version of this, it’s a huge bonus. For example, one application had something like “I know that lots of people are working on different variant of [topic A], but I’m specifically interested in topic A, sub-area X, because of my experience in …” At the end of the day, it all goes back to that list of the points I laid out in section 0, and such a statement provides evidence for many of those points, and I should stop repeating myself at this point.

What IS worth emphasizing here is that you should aim to convey these points as quickly as possible. An “average” application can really stand out by presenting all the relevant information for your evaluators in the most accessible and direct way, whereas a theoretically “good” application can obscure key points in lots of text. If you claim you have a quality, then immediately provide evidence to support this, and say why that matters. It’s basically what they teach in high school English class for how to write an essay, but nobody pays attention to that shit, at least I didn’t. So here it is again. This is true for most formal academic writing, like a paper, but certainly true for a personal statement: I do not want to be guessing who you are and what you’re interested in. Just tell me, then convince me!

I guess it’s also worth mentioning that the statement is not a laundry list of stuff you’ve done, it’s an argument that’s supported by the stuff you’ve done. The argument or claim is: I will be competent / I am interested in doing X, so let me in your school to do it. The evidence is, most likely, “I’ve done X before” or “I have always been interested in X as shown by…”. It’s very difficult to quickly distill what exact point you want to make when the claim is not explicitly stated. I get that people often feel shy or embarrassed in claiming something about themselves, like “I am hardworking”. But remember that the entire point of the personal statement is to convey exactly those points, and you make both of our lives easier by stating it upfront than trying to be modest and let me guess (though obviously try to be tasteful and measured in what you claim). Same thing for the CV: if you’re applying to a lab that does research on or with database stuff, and you’ve worked with databases in a previous job, state it. Personally, I saw a lot of interesting CVs with a diversity of previous job experiences, and to be honest, having performed well at a job is as much evidence of being ready to work in research as anything else. Important and relevant stuff at the top. I don’t know, is this all obvious?

One last thing I already mentioned previously regarding the letters: if you have a long-standing hobby or a community service that you do, especially one that you dedicate a lot of time to and perhaps quite competitive in, talk about it. It may be difficult to properly contextualize it in writing, for a PhD application, because the worry is always that “nobody cares that I’ve been knitting for the last 10 years”. But sustaining a hobby for the in the long term is difficult, and it demonstrates that a person is able to stick to something that they’re interested in for a long time, even through (presumably) difficulties. Assuming you are just as passionate in whatever field of science you chose, this bodes well. Of course, I wouldn’t rely on just this fact to get into grad school, but anything positive helps.

3. Grades and standardized test scores

Not much to say here: good grades (and test scores) are better than bad grades, and that’s not something one can change during the application process. What was surprising to me personally was to realize that, as much as I was a believer in the fact that grades are uncorrelated with success (or survival) in grad school, I still viewed a good transcript (and good GRE scores) very positively. In some cases, it rounds out a good application that had great letters and CV; in other cases, it saved an otherwise unremarkable application from being straight up tossed out. In the end, it’s another metric, and while I think the skills to get good grades in university are mostly orthogonal to doing well in research, some things do overlap, namely: being organized, being able to learn, and being consistent (though one can get good grades without those qualities).

Put it another way: there are multiple ways for a person to achieve a near-perfect transcript. You could be “naturally smart” in the sense that none of the stuff ever challenged you, or you could be a “book smart” person that knows how to study and perform well on tests, or you might actually enjoy the field of your study so much that it was fun to delve into things. These 3 different people will face different challenges when they first start a PhD, and it’s unknown whether they will be able to overcome them. But it’s certainly the case that getting good grades does not directly lead to an easy time in grad school. At the same time, having bad grades doesn’t imply that one cannot do research, and there may be a million reasons why somebody has mediocre grades in university, ranging anywhere from personal issues, working a job, not having found something that’s interesting, or is “dumb” (whatever you want to define that to be). In the end, the transcript is the final and observable outcome that was the result of all those factors, and it’s impossible to guess, from that alone, what kind of person the candidate was and what challenges they faced during their university education. But good grades don’t hurt, and if you do for some reason have some bad grades in a transcript, you should maybe explain why that happened, and most importantly, why that should not imply you are incapable of doing research (and in parallel, point to things that does say you can be a good PhD student).

Finally, and onto the most controversial thing: GRE and standardized tests. It’s difficult to gauge whether a A+ transcript from one school (or country) means the same from another school. Viewed charitably, schools vary in the difficulty of the material they present on a particular topic, and this is true even from professor to professor, from department to department. This is just a fact, and leads to things like taking a specific course in one semester vs. another because a certain professor is teaching it. Viewed uncharitably, some schools inflate grades more than others. Regardless of the reason, the very real difficulty in evaluating a candidate, especially those from different countries, is to gauge how much stock to take in their perfect transcripts. One strategy is to say, let’s just not look at the transcript in either case, since it’s quite subjective. Another strategy is to try to come up with some standardized measure that gets rid of these systematic variations. Yet another is to have someone familiar with the respective systems to do these evaluations, e.g., someone that knows what a 4.0 at Princeton vs. Stanford REALLY means, and which of the universities in Iran are more difficult than others.

The first strategy sounds more fair in theory when viewed within a limited context, but in practice just puts more weight on other, and potentially even more subjective, measures, like the recommendation letters. The third is probably more fair, but it’s simply impossible for any one evaluator to be familiar with at most 3 or 4 schools or systems, compared to as many schools as there are candidates in any batch of applications, and you certainly don’t want to down-weigh a school just because you’ve never heard of it. The second strategy, well, that’s the GRE. Prior to this experience, I would say that I was a mild opponent of the GRE, I just didn’t see it as being really that useful in evaluating the candidate, for how much it costs. But having been on this side, I realized that those numbers are just another set of numbers that provide another view on the candidate—it’s another column in you data matrix. More specifically, it’s yet another chance for a set of candidates to really showcase something positive about themselves. Scoring perfect on the GRE by no means guarantee research success, but it tells me that this person can do tests really quickly in a short time, and probably had to cram quite a bit the month leading up to it (which IS a skill useful in many walks of life). At the same time, understand that these standardized tests are not standardized, or even unbiased, for many reasons. And as such, they should be considered with ample precaution and context such that people are not systematically penalized because of that.

Nevertheless, it’s yet another piece of information, and personally, it gives me another opportunity to view a candidate positively if they had nothing else. For many people, doing unpaid research in their spare time during university is simply impossible, which pretty much eliminates their potential for getting a good letter or publications on their CV. I’m speaking as a person that would have never done research in the summer had I not been fortunate enough to get funded positions through the Canadian government (shoutout to NSERC and the motherland). A Master’s degree (and the associated thesis) mitigates that somewhat, but it still costs money to do a Master’s degree for two years. In the end, I don’t think I have a problem with standardized tests, I have a problem with mandatory standardized tests with an exorbitant price tag. If you have a problem with how much the GRE costs, don’t get rid of the GRE, get rid of your graduate program’s application fee, which literally provides zero information on the candidate other than whether they’re willing to pay 100 bucks. Most people apply to at least 3 schools, that’s your free GRE right there. If you have a problem with the GRE being systematically biased, then you should motion to get rid of recommendation letters too. But at the very, very least, standardized tests are something that a candidate can control, on the timescale of a month or two, and could be someone’s last real opportunity to prove themselves in their application. But then again, I don’t know how many such slumdog millionaire scenarios there actually are, of someone who is really saved by the GRE and didn’t otherwise have good grades, letters, or CV.

So what should you, the candidate, take away from this rant? Not much. Try to get good grades and test scores. Though I guess my one recommendation is that—and this even surprises myself to say—if it is optional for a school, and if it has the chance of being the most outstanding thing in your application, then I’d consider making the investment to do it. But I really wouldn’t worry too much about it otherwise (obviously study and try to do well if it is mandatory).

Final thoughts

During the couple of weeks that I was working on this post, I saw this tweet, which basically amounts to saying “we have no idea how to pick ‘good’ PhD students and our arbitrary criteria are reinforced by confirmation bias”. For the most part, I (emphatically) agree. I think a much better question than “who will do well in graduate school” is “who will work well with me”, as a PhD advisor. The latter question determines the success of the student much, much more, and is a function of both the student and the advisor’s styles, than some homogenous average quality. I have written down a list of qualities up top that I think helps a person do well, but that’s very much limited to my experience and personality, and because I think “being a genius” is not something worth putting as a bullet point.

So why the hell did I write this thing? Let me re-iterate: this post isn’t about being a good PhD student or being competent at research, it’s about how to optimize your application so that you have the chance to do what you want to do in science, by first passing the hurdle of differentiating yourself enough in a batch of 300 applicants. I do believe in those qualities that I listed, but given the chance to talk to someone in person, I would not use any component of the application package to judge that, and I think any advisor worth their salt would feel the same. So for you, the candidate, the challenge is to get through this mass prescreening round to have the opportunity to speak with your future advisor, which is why I have no shame in saying: all else being equal, the best thing to do is to make your evaluator’s life—my life—easier.