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LeslieLee

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  1. Actually I am more interested in computational neuroscience. But yeah I didn't really consider the problem of background matching. Maybe UChicago is not the best place for me.
  2. Thank you for your suggestions! What I am concerned about is that most schools want to see a strong performance in grad-level classes, especially real analysis. I am only going to take these classes this fall, and the semester ends in Dec. If the deadline is very early and the school don't want to see updated transcripts in mid-Dec, then...I am afraid in sense of math preparation, I am not gonna be very strong. But yeah, it is great to see that most school will accept that!
  3. Hi! I am applying to biostatistics/comp bio PhD and MS programs for Fall 2021. I spent two years studying bio and then transferred to statistics. I am kinda of worried about if I am qualified enough for PhD, especially that I didn't take many grad level math classes. I am gonna take some this fall but some schools have very early deadline so they won't see my grades. My GPA is not super high either ( The school I went to is famous for low GPA ). So I am applying to some MS programs as well, in case I cannot get into phD. Please let me know if the schools that I apply are too high or low for my profiles. Thank you so much! Student Type: International Asian Female Undergrad: Ivy Majors: Biology, Statistics Minors: CS Math GPA: 3.73 Math courses: Calc III(A), advanced linear algebra(A-), advanced probability with calculus (A+), Stats(A-), Linear models(B+), analysis (B+),Data Analysis using R, Grad level statistical computing Going to take this fall: grad level real analysis, grad level statistics, probability with measure theory, grad level theory of linear models, numerical analysis CS courses: Java OO Programming (B), data structure(A-), Python (A), Unsupervised Machine learning (A+) Going to take this fall, Supervised machine learning GRE: haven't taken yet, but soon. My expectations are: Q 170, V 160, W 4 Research: 6 month quantitative genetics with a US National Academy of Sciences member (Not sure if this title is gonna help in any way). No published paper 9 month quantitative genetics, mainly using machine learning. One 1st author paper 1 year with computational neuroscience. Present in two conferences. One 2nd author paper, One 1st author paper Letters of Recommendation: PIs of each of my research projects (3 different professors), Dean of the statistics department at my school who taught me statistical computing class. Work experience: 1 semester as a TA for a stats class, 1 semester as a tutor for academic writing Schools: Reach: 1. Weill Cornell Comp Bio phd (Two of my PIs are in this institution, one of them is in the admission committee. I don't know if this is gonna help. They also accepts an updated transcripts for the fall semester.) 2. Columbia biostats phd (also agreed to receive an updated fall 2020 transcript), 3. University of Chicago statistics phd (they have a very late deadline so gonna see my grades in the fall) 4. Upenn biostatistics phd target: 1. Vanderbilt biostatistics phd (they have a very late deadline so gonna see my grades in the fall) 2. UCLA biostatistics phd 3. Upitts biostatistics phd 4. UTexas Houston biostatistics phd 5. Georgetown biostatistics phd (they accept updated transcripts of this fall) 5. UC berkeley, JHU, Harvard, UW Seattle biostatistics MS Safe: I haven't decided, need suggestions
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