open_ball Posted July 31 Share Posted July 31 Here are my stats: 3.97 GPA; major: applied math / statistics Interests: uncertainty quantification, compressed sensing / signal detection, machine learning (broadly speaking), dimension reduction / manifold learning. Relevant coursework: real analysis I and II (my favorite courses I took in college!), numerical analysis, mathematical statistics and probability (2-course sequence), graduate numerical linear algebra course, ODEs, data science programming, cloud computing, ... (all As). Have taken reading courses on probabilistic machine learning, deep learning. Courses left to take: PDEs, regression analysis, graduate real analysis, differential geometry. T25 undergrad (not known for math) Female domestic applicant Other notes: I switched from English major, originally was on pre-law track. Research experience: all tangentially related to healthcare applications, all related to machine learning. Math REU (NSF funded) (topic: computational math-- diffusion model). Paper approved for publication in SIAM undergraduate journal Math REU ( (NSF funded) at top public school for applied math (topic: harmonic analysis / machine learning for signal processing). Have not finished arXiv preprint yet Machine learning research assistant (topic: uncertainty quantification). Will be one of the last authors on a paper. Honors thesis. Topic: have not decided yet. Schools I will be applying to: Duke stats Rice stats Northwestern stats Columbia stats NYU stats UPenn (Wharton) stats Yale stats University of Washington stats Harvard stats Stanford (I am really interested in Emmanuel Candes's work on conformal prediction as well as compressed sensing, but I'm probably not good enough). Two other girls from my school / department who graduated in past years got into ICME at Stanford. An operations research prof at Stanford looked over my CV and suggested I apply to ICME. REU #2 school (program: applied math / scientific computing) Columbia biostats Harvard biostats (Dare I apply???) CU Boulder (applied math) Columbia (applied math) Rice (applied math) Recommenders: My PI (has ties to Biomed engineering, CS, and stats department at one of the schools I've listed); tenured Math professor from REU #1; tenured Math professor from REU #2 -- works in applied harmonic analysis; tenured. Languages: LaTex, Python (specifically PyTorch), R, MatLab. My question: Which programs are unrealistic for me to apply to? Am I qualified to apply for biostatistics if I have taken almost no biology/science classes in college? My past research has been related to biomedical applications. Link to comment Share on other sites More sharing options...

bayessays Posted July 31 Share Posted July 31 Biology/science classes are completely irrelevant to applying to biostatistics programs. You can realistically apply to any statistics or biostatistics program. Your list is a little bizarre in that you have a huge gap in terms of school quality. Your schools are almost exclusively the hardest programs to get into in the top 10, and then you have Northwestern and Rice. I think Rice is about the lowest you should be applying to, but I'd apply to more schools in the 10-30 range because the top 10/Ivys are hard to get into. You can definitely apply to Harvard biostat and any other biostat program - I'd apply to Harvard/Hopkins/Washington (unless you'd rather do Stat at these schools). You're selling yourself way short - you literally have the ideal background and my guess is you'll have multiple options in the top 10. BL4CKxP3NGU1N and Jim VK 1 1 Link to comment Share on other sites More sharing options...

## Recommended Posts

## Create an account or sign in to comment

You need to be a member in order to leave a comment

## Create an account

Sign up for a new account in our community. It's easy!

Register a new account## Sign in

Already have an account? Sign in here.

Sign In Now