Description
This PhD project will investigate how principles of brain computation can inform the next generation of AI, and how AI can help explain neural dynamics. The candidate will develop machine-learning, generative-modelling and foundation-model approaches for multimodal neuroimaging and neural-recording data. Potential directions include brain foundation models, biologically inspired continual learning and synthetic biological intelligence. Based in Monash University’s Computational Neuroscience Laboratory, the project offers an interdisciplinary environment spanning neuroscience, mathematics, computer science and industry. Applicants should have a strong quantitative background and programming experience, preferably in Python and machine learning.
Essential criteria:
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords
NeuroAI; computational neuroscience; artificial intelligence; machine learning; brain foundation models; generative modelling; active inference; multimodal neuroimaging; neural dynamics; biologically inspired learning; continual learning; synthetic biological intelligence.
School
School of Psychological Sciences » The Turner Institute for Brain and Mental Health
Available options
PhD/Doctorate
Masters by research
Time commitment
Full-time
Top-up scholarship funding available
No
Physical location
Monash Biomedical Imaging facility
Research webpage