Advice for pursuing Biostatistics PhD

[nashmash14224]

I specifically signed up for GradCafe to ask this question lol.

 

So my background is a BS in Biomedical Engineering, and an MS in Biomedical Engineering with a focus in Biomedical Imaging. During my MS, I took a course in probability, statistics, and stochastic processes, and was absolutely smitten by the subject. My interest was further piqued after taking a class in computer vision and computer networks and realizing the huge breadth of application statistics has in general (it is obvious that I had never taken a formal course in statistics beforehand).

 

I have realized engineering research is something I would not like to pursue in the future. My original plan was to go to medical school, however obviously that has not worked out for me. To stay close to the clinical field, I would like to pursue Biostatistics, but I do not know if my background is sufficient for doing so. 

 

I underperformed during my undergraduate studies in a top tier engineering school due to an enormous lack of motivation and drive(barely graduated with a 3.0); however my graduate studies (at a renowned university for the social sciences...but mediocre for engineering), went extremely well (3.6 GPA). All the math courses I have taken I scored a B+ or better. I have had over two years of experience in clinical research and have been published in two papers. I also have a year of biopharmaceuticals industry experience. 

 

I was wondering if this would suffice to apply to a well ranked biostatistics program? I am extremely interested in the field, and I know I would be willing to devote my life to this subject. I am just on edge about how I will be able to convince programs to accept me due to my lack of formal mathematics training. Any advice on the field, how to pursue it, etc would be very appreciated. Thank you.

[cyberwulf]

I don't want to sound too pessimistic, but you are facing a really tough road to get admitted to a decent biostat PhD program. The median GPA of students entering top 10 programs is >3.8, and this number is even higher for students entering with a Masters degree (though I don't know your field, in stat/biostat a Masters GPA <3.7 is considered below average). When you add this to the fact that you're lacking in mathematical background, you're going to have a difficult time competing. Your best bet, I think, would be to try to get into a Masters program somewhere decent, and use good performance there (i.e., 3.8+ GPA, strong letters, etc.) as the basis of your PhD application.

[ginagirl]

I think there's also something to be said about research fit- I would suggest if it's something you want to continue with, to look for programs with research focuses in biomedical imaging, etc, and work that in your favor. Figure out what it is that you can bring to the table with the experience that you have, and find programs that can appreciate that. I think that is what would give you the best chance.

Also keep in mind most programs require or strongly recommend certain prior mathematical coursework (usually some amount of calculus and linear algebra).

[nashmash14224]

Thank you so much for the above advice.

 

I might add that I do have a lot of mathematics background (3 semesters of calculus, 1 semester of ODEs, 1 semester of Linear Algebra)....I just don't have any explicit experience with statistics except a single course in probability/estimation theory.

[wine in coffee cups]

I might add that I do have a lot of mathematics background (3 semesters of calculus, 1 semester of ODEs, 1 semester of Linear Algebra)....I just don't have any explicit experience with statistics except a single course in probability/estimation theory.

Not to be a Deborah Downer, but I wouldn't characterize that as being "a lot of mathematics background" for biostatistics PhD admissions. A full calculus sequence and linear algebra are barely minimum requirements at many programs. Quite a few places will want to see a proof-based analysis class too. I agree with the suggestions to consider applying to master's programs first.