Many students in the Computational Brain Science group are enrolled in the Neurosciences Graduate Program at Western University, which is committed to excellence in training neuroscientists. The program provides multidisciplinary training across the breadth of neuroscience and also offers courses to deepen their knowledge in computational methods. Depending on the supervisor, students are also enrolled in other graduate programs, with applications being accepted for both MSc and Ph.D. programs.
Relevant graduate programs:
BrainsCAN Computational Graduate Studentships
We are looking for exceptionally talented and motivated MSc / PhD students for the Fall 2022 intake. Through BrainsCAN funding, we offer a competitive graduate scholarship program in computational neuroscience. Interested applicants should contact one or more principal investigators at Western University whose combined expertise covers the spectrum of computation and neuroscience, and who can serve as co-advisors on the proposed research project. Projects that contribute to increasing diversity in neuroscience at Western University are encouraged. An overview of neuroscience related principal investigators can be found here with the core computational neuroscience labs here.
Please send a single PDF file entitled <LastName>_<FirstName>.pdf to the principal investigator(s) you hope to work with, containing:
- a CV
- a short research statement (max. 2 pages) outlining your research interest and how it fits with ongoing work in the lab
- the name and contact information of 2 academic references
- please state clearly which graduate program (Neuroscience, Computer Science, Statistics, Mathematics, or other) you are applying for.
Contact individual principal investigators as soon as possible, but no later than January 10. The deadline for the graduate scholarship application is February 1, 2022.
For questions about the program, please contact Marieke Mur.
Research project and background
Applicants will propose a research project in computational neuroscience. Suitable projects include, but are not limited to, developing novel methods for neural data analysis, modeling of dynamical systems, and applying machine learning techniques to neuroimaging data in innovative ways. In general, projects should harness computational techniques to provide novel neuroscientific insights.
Applicants with a background in both computational fields and neuroscience are preferred. If the applicant has a background in only one of these disciplines, their research proposal and training expectations should clearly explain their motivation and preparation to transition into computational neuroscience. Applications from researchers who are transitioning from graduate work in the physical, mathematical, engineering, or computational sciences into computational neuroscience are encouraged.