Biostats Profile Evaluation

[cyprusprior]

I'm planning to apply to biostats and some bioinformatics PhD programs this Fall (2013, ie, the program would start Fall 2014). I appreciate any advice or comments you can offer!

 

My goal is to find a "middle ground" between my interests in Biology (originally ecology, shifting recently towards genomics), Statistics, and programming. It seems like bioinformatics might be a good way to go. I'm open to a career path in academia, government, industry, and including international (I want to keep options open a while longer if possible). I am a big fan of the Bayesian approach, and I would rather lean in the computational direction than the theoretical direction. I don't think I'm interested in clinical trials, but not totally sure.

 

- Demographic: late 20s male domestic

- Undergrad: BS Biology, 3.75 GPA, top 20 liberal arts college East Coast. (essentially, premed curriculum)

- Fulbright Scholar in Southeast Asia. Resulted in one publication of field ecology research.

- Currently working full time as a software tester (for the past 5 years). Have learned a ton about SQL, python programming, basic Java, etc.

- almost complete: MS Stats and Applied Math, 4.0 GPA. The program is not proof-based, but heavy in calculus/linear algebra (we used Casella & Berger for Math Stats) and programming skills (R, Matlab)

- MS courses: Probability Theory, Math Stats, Numerical Methods, Stochastic Simulation, Bayesian Stats, Linear Models

- other coursework: Real Analysis I (rigorous proof based summer class, covered basically up to differentiation, but did not cover integration or sequences of functions), Ordinary Differential Equations (at undergrad). I have also completed Machine Learning, Algorithms I, and Optimization courses on Coursera.

- Letters of Recommendation:

MS Bayesian Stats Professor (PhD at top 3 Biostats Dept),

MS Regression Professor (PhD in Stats from second tier Stats Dept)

BS Biology ecology/botany research advisor (very close relationship with this professor)

- GRE: old scores expired, need to retake this summer. Am doing a prep class and anticipate good, but maybe not perfect, scores. Have not taken subject GRE and don't plan to.

 

Here's where I'm thinking of applying:

Biostats: Johns Hopkins, Michigan, Harvard, UNC, UCLA, Emory

Bioinformatics/ Computational Biology: UC-San Diego, Duke

Statistics: Carnegie-Mellon (or maybe Stats and Machine Learning? Can I apply to both?)

 

Places I am not sure about:

Berkeley Biostats- seems too small

UCLA stats/ bioinformatics/ biomath- I am totally confused about how to differentiate between these departments.

NCSU Bioinformatics- not sure about the quality of the program.

Colorado State- Professor recommends it, but seems to be low ranked and not much bio-related research?

UMaryland Scientific Computing- interesting program, but alumni don't seem to be finding good jobs

Penn State, Florida, UC Davis, Texas A&M, U Texas Health (Houston Cancer Inst.)- don't know anything about these really.

 

Places I'm sort of ruling out mainly due to the climate or other "quality of life" factors

Upenn Biostats, Yale Bioinformatics, Minnesota Biostatistics, UWashington Biostats, Columbia Biostats

 

Places I'm sort of ruling out mainly because I think I'm not qualified:

Stanford Biomedical Informatics (such a cool program!), NCSU Statistics, Duke Statistics

 

Thanks again for your feedback!

 

 

[Tronathan]

I am curious about why you ruled out some places but not others?

 

Was Penn because of the neighborhood? Isn't Johns Hopkins also in a high crime area?

Yale? I'm curious why you ruled out this one?

I agree that Minnesota is cold but so is Colorado.

If you ask me, out of all the places you mentioned, Seattle has the highest quality of life. Plus, it is arguably the best program you listed. If you hate rain then it also rains a ton in Florida (maybe more?) plus it gets really hot and humid.

Not sure about Columbia, is it because of high cost of living in NYC? I would argue the same for Harvard, UCLA, Berkeley, maybe even UCSD.

 

I also didn't think that NCSU and Duke for stat are tougher to get into than Johns H, Harvard, UNC and Michigan for biostat or CMU for stat. I may be totally wrong here.  

 

Of all those places you mentioned I have visited Texas A&M, UTHSC-Houston, Florida, Emory, NCSU and UNC and I will be attending UNC in the fall. Feel free to ask if you have any general questions about these.

[timmmythetooth]

You may know this, but CMU will not have a great deal to offer for bio-related stuff, unless you're interested in neuroscience (Rob Kass and others from CMU and Pitt are working on very cool things in in the Center for the Neural Basis of Cognition).  Very nice program in general, though.  I believe you can apply to both Stat and Stat/Machine Learning, but Stat/Machine Learning is very difficult to get into, and I would expect successful applicants to have a good deal of CS background.

 

Like the above poster I find it strange that you would reject UW for quality-of-life reasons, but I'm biased, as I'll be going there next fall.

 

Regarding NCSU and Duke for Stat, my impression is that CMU and Duke are about equally difficult to get into, with the small size of Duke perhaps making it a bit tougher there, while NCSU is easiest (doesn't mean easy, of course!) of the three.  CMU is by far the most attractive of the three to me, but I don't know about bio connections at Duke/NCSU.

[wine in coffee cups]

It sounds like you have a competitive and interesting background, but I would definitely broaden your list to include less selective departments. Is your MS program considered solid, does it have a track record of good PhD placements?

 

From what I know of the research in the UCLA bioinformatics department, that actually sounds like it might be a good fit for you. Duke and CMU stat, not sure about those for more computational genomics-y things? Maybe, but it's not what comes to mind, perhaps too theoretical for your tastes. Also, I think you'd have a much easier time getting into NCSU than CMU because of its size, even though it's a strong department.

 

Your light math background could be an issue both in getting admitted and surviving PhD-level coursework. My guess is you'd get more leeway from non-statistics departments. The real analysis summer class sounds skimpy, but fortunately for you grad schools probably won't know that. You didn't mention it, but I assume you have linear algebra on your transcript somewhere? That's a pretty firm requirement at most places and I don't know that obviously needing to use it in other classes would count. The Coursera classes aren't going to matter for anything besides personal edification.

 

Utterly baffled by your climate/quality-of-life rule-outs. Seattle is awesome, love it here! Baltimore and Boston but not NYC, Minneapolis, or Philly, what? And I think any proper city is going to offer more for someone in his late 20s/early 30s than a college town like Gainesville, College Station, or Chapel Hill so I'm surprised you seem to be leaning that way. But of course if you already have firm (and reasonably informed) opinions, no point wasting your time and money.

[cyberwulf]

I think your profile will play well in biostat and comp bio departments; you're probably a little thin on the math side to crack the top stat departments. 

 

I don't know much about comp bio/bioinformatics programs, so will focus on the biostat side, where I think you will be competitive for admission at all the places on your list. Strongly encourage you to consider applying to UW, since they seem to be going "all in" on the big data wave, and have a lot of exciting young faculty. And if you're interested in Bayesian methods, most of Minnesota's highest-profile biostat faculty are Bayesians.

 

My biostat list for you would probably be:

UW, Hopkins, Michigan, UNC, Minnesota, + 1-2 safeties (I think UCLA and Emory qualify, given your profile)

For stat, I would throw apps at NC State and CMU. I wouldn't bother with Colorado State.

Edited May 15, 2013 by cyberwulf

[Igotnothin]

Cyprusprior,

 

I think you've got great creds and should shoot for the moon. Because even if you miss... well you get the picture.

 

Harvard and UW are the consensus top-2 for biostats, and I think you're in great position for either (this is coming from someone who got rejected from both!). You've got a really well-rounded and impressive application. Very good math background, real-world experience, great programming skills, international experience, letter from well-known biostats profs, a publication. OK now I will stop flattering you. 

 

Everyone I know at UW loves it. Seattle is a great city and the biostats department is as good as any. Also they have a pretty big department, so you can expect to be a part of a reasonably sized cohort, which is nice. Based on the department reputation and Cyberwulf's info on UW's big-data emphasis, you might take a closer look at their program. 

 

I know much less about non-biostats programs, but I will say that in general applicants tend to under-estimate themselves. I can't tell you how many people I met on the interview trail at top programs who really didn't expect to be there. You might as well put down the $60 or whatever it is to apply to programs like Stanford... it's not like 10 years from now you're going to look back and regret applying.

 

I also think you should consider $$. You'd be surprised at the heterogeneity in stipends across top schools. Last I checked Harvard was $28,500, UW $21,000 (increasing this year). Hopkins $22,000. If you end up with 2 programs that you're really split between, a $7,000 difference in stipend might sway you. That's some good beer money right there.

 

Good luck!

Edited May 15, 2013 by Igotnothin

[cyprusprior]

Everyone, thanks so much for this excellent feedback. I didn't mean to give the impression that I was truly "ruling out" any program. Rather, I just had a gut feeling that I would not like living in certain places (and thus be not as productive) based on vague childhood memories of visiting them. Also, I love hiking and the outdoors, and am pretty frugal. I have noticed in myself that I am much more mentally focused in sunny climates rather than dark ones (temperature is less important). That's why I was discounting places like Seattle and Minnesota and considering Texas/Florida places (the data I used is here: http://www.ncdc.noaa.gov/oa/climate/online/ccd/avgsun.html ). I was hoping that if there really was something special about a particular program I was overlooking, that folks with a better perspective than me would be able to convince me to change my mind. Clearly based on everyone's feedback, I should not have ignored UW, and I'll have to think harder about Minnesota. Honestly, I just wish that there were more good universities in sunny parts of the country!

(and to answer "wine in coffee cups"- yes, I did take Linear Algebra)

Edited May 15, 2013 by cyprusprior

[cyberwulf]

Well, if you like hiking and the outdoors, Seattle is pretty tough to beat. Though there's no doubt they've got a bit of a sunlight problem.

 

While quality of life *is* important for a graduate student, I generally advise people to keep an open mind geographically and not let preconceived notions weigh too heavily on the decision-making process. For most, the key to a happy grad school experience is being in a department where they feel motivated, challenged, and encouraged. Though I have no evidence to support this, I suspect that students who make grad school decisions based mostly on location and other factors unrelated to department quality are the most likely to be disappointed in their choice and eventually burn out.

Edited May 15, 2013 by cyberwulf

[wine in coffee cups]

I have noticed in myself that I am much more mentally focused in sunny climates rather than dark ones (temperature is less important).

SAD light boxes were all the rage when I was an undergrad in rural MN. Get one of those suckers on Amazon and you're set even in the dark frigid north.

[cyprusprior]

Hey everyone, thanks again for the advice and encouragement. I just took the GRE yesterday and got a 166V, 170Q. Needless to say, I'm very pleased with the scores and am looking forward to starting applications soon!