Statistics PHD Preparation Advice

[StatsJ]

Undergrad Institution: NC State
Major(s): Statistics
Minor(s): Math
GPA:  4.00 (About 3.85 without A+ inflation)

Type of Student: Domestic White Male

Current Research Interests: Machine learning, Bayesian statistics

Research Experience:  

• NSF Data Science REU this past summer in Texas
• Data Science research lab on campus: Analyzing disinformation pathways and influence on social media platforms via VAR modeling and NLP techniques (working on this for about a year now; submitting a manuscript in the next couple of months)

 

Coding Skills: 

Python, R, SAS, SQL

 

Other Activities or Jobs: 

• Quantitative Analyst for university baseball team
• Interning as a Data Engineer at a large FinTech company next Summer

 

Math/Statistics Grades:  

Calc I (A)
Calc II (A-)
Calc III (B)
Intro Stats I (A+)
Intro Stats II (A+)
Intro to Advanced Math (Intro to proof-based math) (A+)
Linear Algebra (Proof Based) (A-)
Statistical Computing (B+)
Experimental Design (B)
Regression Analysis (A+)
Mathematical Statistics I (A+)

 

Plan to take:
Mathematical Statistics II 
Graduate level Linear Algebra
Advanced Statistical Computing
Real Analysis

 

I'm currently a junior and looking for an assessment of my profile and some advice for identifying target programs to consider applying to next year (Fall 2025 cycle). Through my research experiences and stats/math courses I have become highly interested in machine learning and some of its theoretical underpinnings.  The process of finding the right fit for a PHD and gauging an application seem somewhat tedious so any thoughts or advice is appreciated.

[bayessays]

Start with US News, I'd focus mostly on programs in the 10-60 range.  See what locations you like and look at those department pages - most programs have a faculty page that will list research interests.  Most programs will have one or two faculty that focus on Bayesian stuff - programs that focus on Bayesian stats include Duke, Texas, Missouri, Iowa.  You'll have to dig a little harder depending on what exactly you mean by "machine learning."  Also look at biostatistics programs in the top 20, as your profile will play well there.

I'd talk to your professors, and focus on securing good letters of recommendation from research advisors - you go to a top 15 stats program, so try to take advantage of the vast connections of your department if possible.