Applying to Life Science PhD Programs in 2015
- 13 minsApplying to Life Sciences PhD Programs in 2015:
Gaining acceptance to a top-rated life sciences PhD program is an undertaking.
Unfortunately, I’ve found that some undergraduate institutions lack advisers to help guide students in this process. There is a metric ton of information re: graduate school on the web, yet during my application period, I often had to spend hours piecing together the bits that were relevant for my field.
This post is my attempt to place everything I learned during the process in one easy to digest web-page. Some sections will only be applicable to students at an early stage; feel free to skip over them. My writing isn’t worth wasting too much time on.
Before Applications
How to Improve on Paper
If I can only hammer in one point, it’s start early. The best way to improve your chance of acceptance is to improve yourself as a candidate. A clever statement of purpose and a well written research summary cannot make up for a lack of experience.
So, how do you improve yourself as an applicant during your undergraduate years? I think it comes down to three things, ranked in order:
1. Gain research experience
The vast majority of your time as a PhD student will be spent conducting novel research.
Logically, participating in research as an undergraduate is the best preparation for graduate school. Not only is research experience a key application metric, but it’s important to gain first hand experience with the day to day life of a life scientist before jumping into a 5 year commitment. Entering a PhD program without sufficient research experience is like proposing on the first date.
It’s important that this experience be genuinely educational, and not simply a line-item on your CV. You should walk away from a day in the lab with your synapses firing on all cylinders, a little bit embarrassed by your lack of experience, and a whole lot of motivated to understand the world around you.
The specifics of this topic (how to find the right lab, how to ensure you’re learning, etc. etc.) really deserve a more in depth discussion.
The best advice I’ve found on these topics is contained in a two part Nature Reviews article by Jonathan Yewdell. His writing has the humorous efficiency of a Vonnegut piece. I highly recommend reading through both sections regardless of your current academic status.
2. Build meaningful relationships with senior investigators
The best way to develop a scientific mindset is under the direction of a mentor. Ideally, you’ll actually build relationships with more than one.
Training as a scientist is primarily about learning how to think, how to collect evidence and synthesize it to form rational conclusions. It’s definitely possible to develop scientific thinking independently, but I’ve found that having a good mentor’s guidance makes the whole process a lot more efficient. More so than practicing any benchtop technique, your training should prepare you to deconstruct a problem into its component pieces.
These relationships should be authentic. Do not seek out guidance from a particular investigator merely because you believe a recommendation letter with their name on it will reflect favorably upon you. Seek out mentors who align with your scientific interests, who approach problems in an interesting way, who are approachable as human beings.
Again, you don’t need to find all the expertise you seek in one person. Seek out and cultivate multiple mentors.
Come time for applications, these organic relationships will easily translate into recommendations for graduate school.
3. Excel academically
This part you already know how to do. Earn high marks in your courses, do well on the GRE. Etc.
While graduate programs aren’t as strict about grades as some other post-grad career paths, you don’t want to give them any reasons to worry. In general, if you’re genuinely learning and enjoying your studies, your grades will not be something you have to explicitly worry about. Most top programs have a GPA “cut-off” somewhere between 3.0-3.4, or none at all. I’ve heard from some admissions coordinators that even these cut-offs are somewhat malleable; if a student is bright and interested and equipped with excellent laboratory experience, they won’t sweat your GPA too much.
That said, keep your grades up to avoid any application red flags, especially in your core science classes. For life sciences programs, this generally means biology and chemistry courses.
As for the GRE, there are five pounds books (no, literally) on how to do well. I’m certainly not an expert.
My limited experience suggests that preparing for standardized tests is really an individualized process. Methods that work for one person don’t necessarily transfer to another.
I suggest taking the GRE PowerPrep practice test, reviewing your scores, and making a study plan from there. You’re a scientist after all, why not collect some preliminary data to inform the design of your study strategy?
As for scores, I’ve been told by knowledgeable individuals that you want to shoot for 160+ on each of the sections, ideally above 163. Again, this is by no means a hard cutoff, but “163+ = very good” should be a decent heuristic for self-evaluation.
Determining Where to Apply
Make a List, Filter it Twice
When it came time to actually start filling out applications, I had a hard time identifying target programs. Maybe I’m the only one who wasn’t born knowing which specific PhD program at which institution they wanted to join, but I’m going to guess a few other people are unsure too.
Several senior investigators advised me to apply for 5-10 programs. Personally, I shot for the upper end of that range, partially out of fear and partially to delay myself from having to make any big decisions. From my experience, 10 programs was a bit too many, so long as you are being realistic with selections given your research experience and academic background.
Here’s how I generated my top 10 list.
A similar process might be useful for you:
- Determine your research interests. What papers most excite you?
- Make a list of PI’s from these publications, along with their institution.
- Filter for institutions with multiple investigators within your field of interest.
- Filter these institutions based on personal factors (where you’d like to live, recommendations from mentors, etc.)
- If absolutely necessary, sort these by rough program ranking using a source like US News & World Report. Ranking is certainly not the number one priority when searching for a PhD program, and these rankings are certainly subjective. That said, if you have too many programs on your plate, ranking can act as a final siv.
Seek out advice from your mentors regarding the training environment at each institution.
- Is graduate training a priority?
- How often do their graduate students publish?
- How large is the program? Where are their alumni now?
- Do they support your desired career track through coursework or campus organizations?
Some of these questions have rather objective right & wrong answers. Hopefully, your graduate program of choice will have a decent publication record for its students.
Other factors are more subjective, such as program size. Some students thrive in large programs with open-ended curriculums, while others prefer a more intimate cohort and structured coursework.
Once you’ve sorted through enough faculty profiles to write a decent Onion-esque parody, it’s time to select your targets and start writing essays.
The Essays
There’s already a ton of stuff on the web about how to write a lucid personal statement, so I’ll try not to commit too many tautologies. I found the Purdue Online Writing Lab guide to personal statements to be helpful.
There is little I can add to that excellent resource, but I do have a practical tip you might not see elsewhere.
Try to localize program specific information to one or two paragraphs.
While it may sound like a lazy move, this allows you to have as many people as possible review the “core” of your personal statement. You’ll soon find it can be difficult to get in depth critical feedback on your essays, and you’ll want to subject your friends & PI to as little of this torture as possible.
By placing your program specific changes in one place, you can reuse your pristine, artisanal-free-range core paragraphs with little worry that the changes will require extensive review.
Some of the programs I applied to also had a second essay focused purely on your research experience. This one is fairly straightforward. I had several projects and merely described them in chronological order. In my case, one project fed into another, so I tried to tell that story to build a bit of a narrative.
It may seem obvious, but make sure not to reiterate information between the research experience essay and your personal statement. You had a limited number of words with which to catch a reader’s attention, try to introduce new information rather than reiterating the same point.
If you have any rough spots on your academic record, this is where you should address them. After going on interviews, I’ve found that admissions committees were very understanding of most common concerns, like poor grades due to medical issues, or just a really difficult semester. In light of that knowledge, it seems best to be completely honest with the committee. These are incredibly smart people who have been around the block. I wouldn’t try to weasel out of anything, just address your concerns in an honest and articulate manner. Of note, some applications had a separate “Write any concerns here in < 500 words” section.
As most applications themselves will note, make sure to highlight how you’ve sought out research experiences if they’re not available at your home institution in the traditional sense.
Once you have your essays written and copiously edited, it’s time to look for fellowships.
Fellowships
There are several competitive fellowships available to fund students during their doctoral research. Obtaining an independent fellowship can provide greater freedom when choosing a lab, as funding is less of an issue (I have heard a joke that fellowship students are in high demand, as they are essentially “free labor” from the PI’s perspective). I’ve also heard of students using a fellowship award to change an admissions decision from rejection to acceptance — this may be because the initial rejection was due to funding, or because the difficulty involved in winning a fellowship like the NSF serves as a positive signal of the student’s competence.
Before I get into it, I’ll note that the majority of what I have to say is covered in an excellent post by DJ Strouse. His post is lively and informative, I highly recommend reading through it. Unfortunately, his website was down when I went to grab the link, so here’s a cached version from Archive.org. Most of what I have to add pertains to life science specifics.
I’ve found that life science PhD students primarily qualify for three major fellowships prior to matriculation. There are fellowships through the Department of Defense and Department of Energy mentioned in the blog post linked above that seemed to me a bit out of scope for what I consider a typical life sciences PhD applicant.
The three I think are definitely worth writing:
1) The NSF Graduate Research Fellowships Program a.k.a. “The NSF”
The NSF provides three years of support for PhD work. The application is composed of two essays: a personal statement and a research plan. The personal statement is similar to those for applications. The research plan is basically a mini-grant application that I personally thought was a lot of fun to write.
I found Alex Lang’s blog post on writing the NSF to be very helpful.
In addition to the linked post, there are plenty of other NSF Fellows who share their tips. As of right now, the NSF results from my cycle haven’t been released yet, so you’re better off taking their advice than mine.
One thing I learned during interviews that I wish I knew before:
The Research Plan section should be similar to a mini-NSF grant. Unbeknownst to me at the time, there are key differences between writing an NSF grant and an NIH grant with regards to the tone and objectives. Since I only had experience with NIH grants, I may have botched this distinction a bit.
What are those differences in tone and objectives? This is another point where I defer to the experts. You’ll find plenty of resources online describing how to optimize a life sciences grant for the NIH vs NSF. If possible, I’d talk to your PI or another PI you’re on good terms with regarding the finer points of NSF grant writing. If they’re really generous with their time, try to get said PI to review your Research Plan while you write it with this in mind.
2) The Ford Foundation Fellowship Program
I missed the deadline before I found out about this program, but plan to apply next year. I was asked about it a few times on my interviews, so admissions committees are definitely aware of the program and recognize the competitive nature of the fellowship.
The Hertz provides five years of support from a private foundation. The application process is famously a bit James Bond-esque, scheduling short notice interviews in posh hotels. I also missed the deadline for this, but plan to apply during my first year of graduate study.
I’ll refer back to DJ Strousse’s post linked above for advice on this one.
Hit Submit
It’s incredibly nerve wracking. Immediately afterward, incredibly relieving. Pat yourself on the back for all your hard work, drink more coffee than you should later than you usually allow yourself, watch a funny goat video.
You deserve it.
Personal Notes, Concerns, & Rotten Tomatoes
I eventually interviewed with these programs:
- Harvard BBS
- Johns Hopkins CMDB
- MIT Biology
- Rockefeller University Graduate Program
- Scripps Research Institute Graduate Program
- Stanford Stem Cell Biology & Regenerative Medicine
- UC San Francisco DSCB
If you have any questions about these interviews from a recruit’s perspective, shoot me an email at jacobkimmel@gmail.com.
If you think this post is stupid — great! Tell me how to improve it in an email.
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Jacob C. Kimmel
Co-founder & Head of Research @ NewLimit. Interested in aging, genomics, imaging, & machine learning.