BabyDietCoke

Thank you for the responses and advice. I think I will spend the last year at my M.Sc program taking courses in the CS department (I've been true most of the sequences being offered next year) and try to build up more of an understanding of algorithms and perhaps ML (from an implementation standpoint). Side question, is it worth taking the Math GRE? I've taken it before when I was less mathematically mature and did horrendous, like 60th percentile, but that was when I haven't taken much math yet. I think I can hit above 80 percentile, but I don't know how vital the Math GRE is for Statistics programs compared to when applying for Pure Math programs.

Student Type: Domestic student Applying for: Applied Math and Statistics PHD Fall 2022 Undergrad: Relatively Unknown Liberal Arts Major: Biochemistry and Economics, Minor: Mathematics GPA: 3.7 (Biochemistry 3.8, Economics 3.85) I had a late encounter with mathematics my Senior year and completely redirected my focus towards Mathematics. Along the way I've found an affinity for applied mathematics (scientific computing stuff) and statistics (on the theory side). As such I'm a pretty non-traditional student, I won't be including the many biology/chemistry courses nor the plethora of economics courses I have taken (it feels pretty irrelevant now, just fun stuff to know I guess). Anyways, I'll include some of the courses I took during a gap year at my local top 30 university before starting my Master's at a top 50 liberal arts program. Unfortunately, I won't be able to take many more courses directly aligned with statistics (perhaps an Intro to ML course) as I have ran out of courses that I can take that I offered this coming school year... Master's: Mathematics GPA: 3.99 (Over 11 Courses for the Past School Year/Summer) Undergrad Math: Calc 2/3 (A-/A-), Linear Algebra (A), Intro Statistics (A), Intro to Proof (A-), Abstract Algebra 1 (A), Complex Analysis (A), Abstract Linear Algebra (A-), Real Analysis 1 (A), Real Analysis 2 (A), Topology (A-), Numerical Analysis (A), Numerical Linear Algebra (A+), Probability Theory (A+), Mathematical Statistics (A+), Differential Geometry (A), Mathematics of Data Science (A), Topological Data Analysis (A). Graduate Math: Abstract Algebra 1 (A-), Measure Theory (A-), Complex Analysis (A+), Uncertainty Quantification (A), Markov Chains and Mixing Times (A). Remark: The A+ are quirks of my current institution, they do not impact GPA, but serve as indicators of maintaining above a 98%/strength in coursework Planning to Take (At Least Up to Fall): Algorithms, Computational Geometry, PDE 1, Graduate Numerical Linear Algebra, Graduate Numerical PDEs Research: Starting this summer, part of Master's Thesis. Focused on differential equations on Fractals. GRE: 170Q, 164V, 6W Letters of Recommendation: Three different letters of rec, one with who I am doing research with over the summer. (They all have a strong connection with some departments I am considering) Applying to: I don't know, yet General Questions: What range of schools should I be considering for PhD programs (Applied Math or Statistics)? Are there any gaps in my coursework or application? I fear that my weakest part of the application will be a lack of strong research experience... I wish to apply for PHD programs in either Applied Math or Statistics because I have become really interested in the ideas of applying Harmonic Analysis to estimate underlying densities, high dimensional probability, as well as scientific computing as a whole (extremely interested in the use of tensors for numerical multilinear algebra). I'm still figuring out the precise direction that I am most interested in, it's all so cool!