Advice on Application Preparation MS/PhD Application (Fall 2025)

[Kaleidoscope3910]

Hello! So I have a somewhat unconventional background because I have been out of school for some time (since 2021) due to personal family issues and a medical problem (which has now been resolved).  I mostly hadn't been working during that time besides some part time TA work in linear and computer science.  I have pretty much no research experience in statistics/mathematics, and I wanted to ask the following questions (because I have had different conflicting advice from different professors):

1. Should I try to look for more research experience to make myself competitive for the schools in mind I listed below and given my portfolio? Or should I focus more on developing my academic background in math (such as auditing 3rd/4th year statistics courses in the fall)?  I was considering looking for positions that start in the fall this year, after I've had a chance to better brush up on material that would be necessary.  It is difficult however, given I'm not in undergrad anymore.
2. If it is recommended, given I'm interested in potentially doing theoretical research, how important is it for that research to have some theoretical component to it? Or would an applied position still help?

Here is my full profile below:

Undergrad Institution: Canadian University (top 20 for statistics apparently, top 25 in general according to QS)

Major(s): Computer Science, Neuroscience and a minor in statistics
GPA: 3.95+/4.00

Type of Student: International (Canadian) Asian Female

Research Experience: Worked at a research co-op at a hospital in an unrelated field, part of an undergraduate research group in CS reading and presenting weekly papers, research course in psychology, was part of a literature review in CS education (but really not relevant to the area I'm applying to) and presented a poster of it at our school.

Pertinent Activities or Jobs: TA'd for theoretical linear algebra I & II for several years, TA'd for social and information networks (a computer science course) and computer networks

Letters of Recommendation: I have 3 solid recommenders, 1 from the head of the CS undergraduate research group, 1 from the linear algebra professor I TA'd for and one from a theoretical statistics professor who is helping me learn real analysis at the moment.

 

Courses (I got A/A+ in all): 

Statistics: Introduction to Probability (2nd year), Introduction to Statistics (2nd year), Introduction to Applied Statistics (3rd year), Probability & Stochastic Processes (3rd year),

Math: Discrete Math (1st year), Calc 1 & 2 (1st year), Linear Algebra I (1st year) & II (2nd year), Multivariable Calculus (2nd year), Real Analysis (currently self-learning with the help of one of my recommenders)

Relevant CS: Machine Learning (3rd year), Algorithms (3rd year), Computability & Complexity (3rd year)

 

Programs Applying: Statistics PhD in the US & Canada + Statistics/CS Masters in Canada & Europe (as a backup)

Research Interests: Foundations of statistical theory (particularly looking at Bayesian vs. Frequentist ways of approaching statistics) or statistical theory behind machine learning algorithms (I apologize if this is a bit general at the moment, I do intend to look into specific papers more as I dive deeper into the academic material - which is another reason why I'm wondering if it is worth spending time trying to find a relevant research position, rather than improving my statistics knowledge)

 

Schools in mind:

- PhD: Any of the top 20-30 in particular considering Columbia, Carnegie Mellon, Harvard, UChicago, UCB, UPenn, UCD, UW, Duke (in approximate order of preference but not solid yet) + of course UofT given my undergrad
- Masters: UofT (applied computing), McGill (statistics & CS), Oxford (statistics) but these are not as relevant, more for backups

 

Long Term Goals:

- Academia in a ~top 20 institutions, not necessarily research focused given the competition, as I enjoy teaching and wouldn't mind taking an equivalent to a teaching stream position (which UofT in particular has) somewhere in a big city in the US

Edited April 15 by Kaleidoscope3910
Fixing a few details

[bayessays]

You say top 20-30, but your list is basically the 10 hardest programs to get into (except UC Davis, which I think is a reasonable target).  Your grades are obviously good, but I don't think there's a lot that makes your profile stand out.  Your math background and research are below average for people accepted to these schools. I'd classify all of these schools as big reaches, except maybe UCD which I would put in the "possible but not guaranteed" category.

If you don't want to go into a research-track job, then going to a program in the top 20 is not by any means required.  I think your best options are to either lower your expectations and apply to a much broader range of programs (there are many great programs all throughout the top 50 and even below the top 50!), or if you are not in a rush, get a master's and get some more background and research experience.