strawberrychocolate

Hey, thanks for commenting. Some more information: I'm international student doing my undergrads and grads studies in the US. Undergrad: BA, Top 30 LAC (Statistics) near Boston -- taken real analysis, math stat, linear algebra, proof-based discrete, linear, computer science Grad: MS, Top 10 Biostatistics, Ivy League Research/work experience up to the point (in chronological order): 1. Research on constructing hierarchical copula models with school professor 2. Summer research in Biostat at a well-known/prestigious cancer research hospital studying applications of joint model for survival and longitudinal data. One LOR from my supervisor, a junior-ish researcher who published in JASA, Biometrika, Biometrics, Statistics in Medicine, etc. Our interaction was not few, due to covid, but I can potentially ask for a LOR from the program director, who is now my best friend/go to person. 3. Summer research in Applied Maths (program funded by NSF) doing deep learning and neural networks (1 conference paper NeuRIPS) 4. Summer internship at a well-established pharma company. One LOR from my supervisor, who left his professorship at a Top 1 Biostat Uni. 2 months before my internship. 5. Research with my current advisor, a premier expert (that's what people call him) in survival analysis with whom I published the JAMA and potentially Stat Med papers with. One strong letter from him (he's incredibly supportive and has always had my back) I'm confident that my LOR's will be strong. However, at the end of the day, I'm still international and not eligible for NIH fundings or training grants. This fact hit me hard when I applied for biostat PhD 2 years ago. I received fully funded PhD offers in statistics elsewhere at that time, but decided to go with my gut and ended up where i am now. MS courseworks shared with PhD students, doing CB. Perfect GPA but due to grad school grade inflation, don't know if people really care. My questions: 1. Where do you think I'll get a good/decent shot? I aimed too high last time so I want to be careful this time. 2. Will I still be grouped in intl students applicant pool? Competing with folks who did their undergrads abroad and basically took measure theory in their sophomore year... 3. Given this application, do you think working as a full-time research assistant/biostatistician at a research university for 1 or 2 years with more applied papers can boost up my chances by a lot and is it worth it? Thanks!

Hello experts, I'm graduating with an MS in Biostat from a top 10 school and have published a research letter in JAMA (2nd author) and potentially 1st author paper in Statistics in Medicine (from my MS thesis). I also have a peer-reviewed conference paper in NeuRIPS. MS courseworks include casella berger. With these under my belt, where do you think I stand a good/decent chance at?

@trynagetby Thanks for your perspective! I had Real Analysis, Discrete Maths and Linear Algebra during undergrads, but it's LAC so I don't know how much they weigh. Please correct me if I'm wrong but I thought maths courses matter when undergrads apply for PhD right off the bat, but once students enter grads school, courses still matter but not so much as the school name and research experience; especially in my case when I'm also taking PhD courseworks. Aren't most biostat programs using Casellar and Berger for their prob/inference and qual exam? Thanks!

MS Biostatistics student looking for advice! Undergrad: top 30 LACs -- Statistics, Data Science (summa) Grad: MS Biostatistics Ivy League (not Harvard) Type of Student: International female GRE General Test: Q:170 V: 160 W: 5.0 Applying to: Biostatistics PhD Research Experience: Right now, projects on survival analysis (both applied and methodological) with a senior researcher -- not sure about potential publications! During undergrads, did summer research at a well-known cancer hospital and an institute for applied maths, and 2 year research at school. Letters of Recommendation: Two faculties with whom I'm doing/planning to do research with at grad school; one might be from profs teaching classes or undergrad studies who knows me very well Grad coursework: Same core coursework as PhD students -- using Casella and Berger for Probability and Inference. Have the option of taking the qualifying exam after 1st year (this coming June) with PhD students Publications: one conference paper on machine learning/applied maths from undergrads summer research. one coming up on using nonparametric tests for an applied project. Co 1st author for the former. Plan to apply: UPenn, BU, Columbia, Yale and maybe Harvard -- I want to stay in the northeast, New England preferably Can someone give me advice on the my school list? After my PhD I might go back to Asia where people care a lot about prestige and brand name of the school, rather than dissertation advisors. I realize this list is ambitious and would appreciate if someone can recommend some "safe" schools. Many thanks!