Join the Lab
Interested in joining the lab?
We are not currently recruiting undergraduate students. When we are recruiting undergraduate students we tend to work with students who have advanced coursework in statistics (with at least a full course in regression) and experience with statistical computing and data analysis software.
We will be reviewing graduate student applications for the Fall 2025 admission. To apply to work in the lab as a PhD student, submit your application through the UBC Psychology Department. For general information on the application process examine the information here. For specific information about applying to the quantitative area go here. Other common questions we receive:
Are international students accepted?
Yes the lab can accept international students.
Is the program at UBC funded?
Yes. The program at UBC is fully funded, the length of funding depends on admission into a Masters or Ph.D. program. There is more information on funding here.
I saw the GRE is optional at UBC, do I need to take it?
It is strongly recommended that students applying to UBC's quantitative specialization take the GRE. The GRE provides necessary information about preparedness for the program, particularly in the absence of advanced course work and extensive research experience. Some students have a strong interest in studying quant methods but developed this interest too late to take advanced coursework or complete independent studies. In these cases, the GRE can be an important part of the application, but we recommend all applicants take it.
What kind of research interests are a good fit?
See the publications page of this site with an eye to papers authored by students and Dr. Flake's google scholar page for recent published projects in the lab.
In general, the lab works at the intersection of psychometrics and open science.
What kind of experience and skills do I need to join the lab?
The minimum requirement for the lab is to have an interest in developing and refining methods for use in psychological measurement. Applicants are not expected to be experts in the methodologies when they apply, so a specific set of courses or training is not required. However, students who have taken advanced statistics or math classes generally tend to be more prepared for the program than those without. Experience analyzing data using statistical software is a strength (e.g., R or SAS programming skills) as well as strong written and oral communication skills.