We are looking for a PhD candidate to undertake novel research at the intersection of cognitive neuroscience, computational neuroscience, and artificial intelligence.
Topic
The PhD research topic will focus on understanding key mechanisms that enable specific cognitive functions in the brain, such as language comprehension, using a combination of computational neuroscience, machine learning, and experimental cognitive neuroscience techniques. The student will develop novel integrations of mechanistic physiological and generative AI-based theories of brain organization, and test these by designing, conducting, and analyzing experiments using advanced neuroimaging and neurostimulation technologies (EEG, fNIRS, TMS, MEG, fMRI, including mobile w/ VR/AR integration).
Location
The student will be jointly supervised by:
Dr. John D Griffiths, CAMH KCNI & University of Toronto, Canada
Dr. Mariya Toneva, Max Planck Institute for Software Systems, Saarbrücken, Germany
This position is jointly hosted by the University of Toronto Max Planck Centre for Neural Science and Technology and the Max Planck Institute for Software Systems in Saarbruecken, Germany. The PhD student will spend time in both locations, deriving full benefit from the two co-supervisors’ complementary scientific expertise, academic environments, and local infrastructure. The PhD degree will be officially granted by the University of Toronto (Institute of Biomedical Engineering). All research will be conducted in English, and proficiency in German is not expected or required.
Background
Candidates must have a strong computational and quantitative background, and must have experience with programming in Python. Experience with designing, conducting, and analyzing data from neuroimaging (EEG, fNIRS, MEG, fMRI, TMS) experiments is preferred, but not necessary if a strong aptitude and motivation to learn can be shown. Proficiency in spoken and written English and scientific writing is required. Demonstrable knowledge of and interest in the fields of cognitive and computational neuroscience is essential. Applicants should familiarize themselves with the two supervisors’ respective research programs and main recent publications, and indicate what from this work is particularly in line with their academic interests (see website links above and contents therein).
Apply
To apply, please send an email to both of the prospective supervisors (john.griffiths@camh.ca and mtoneva@mpi-sws.org) by January 31, 2024 with the following:
- updated CV
- description of your relevant background and motivation for applying for this position
Communicating initial expressions of interest sooner rather than later may be advantageous.
Additionally, candidates will be required to submit an official application for a graduate position at the University of Toronto Biomedical Engineering department by February 29, 2024.
To learn more, visit https://bme.utoronto.ca/prospective-student/admission-to-graduate-studies/.