Prospective PhD students
Our lab is growing, with several PhD positions available over the coming years. Join us if our research speaks to you!
For students interested in starting in September 2025, I will be reviewing Ph.D. applications in the upcoming cycle (deadline: December 1, 2024). Prospective students can apply through the UCLA Communication PhD program. Please feel free to reach out to rdubey@princeton.edu if you wish to apply and want to make contact beforehand.
Ideally, my lab will include students of diverse expertise: (1) 1-2 students with background in cognitive science, (2) 1-2 student with climate policy interests (e.g., background in sustainability, policy, economics), and (3) 1-2 students who are fluent in reinforcement learning or machine learning. What will distinguish our lab is that pretty much everyone in it will be interested in human behavior and climate change, and will have strong quantitative training and coding skills.
Prospective students should have a strong interest in working on climate change and doing basic research in cognition, along with a solid technical background. This includes experience in areas such as web development, data analysis, mathematical modeling, or machine learning. While a strong foundation in cognitive science is preferred, we are always excited to hear from people who would bring new experiences.
Additional resources and useful information
Applying to graduate school:
Here are some excellent resources on applying to grad school and writing a strong application: [1], [2], and [3].
Learning programming skills and computational modeling:
Getting started with programming and computational modeling can feel overwhelming. Here are some resources that are concise and well-explained to help anyone get started.
- An extremely concise and well-explained Python bootcamp, by Justin Bois.
- Russ Poldrack's Statistical thinking of the 21st century is a great free, online book to learn basic probability and statistics
- Neuromatch Computational Neuroscience is perhaps one of the best bootcamps on getting started with computational modeling.