Advanced statistical inference and machine learning for neural modelling, monitoring and imaging

Monash University, Australia

Updated: about 5 hours ago
Location: Melbourne, VICTORIA
Deadline: The position may have been removed or expired!

The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological variables such as network connection strengths between neural population networks underlying brain activity. We work with different physiological data modalities such as intracranial and scalp electroencephalography and magnetoencephalography data to infer and image previously unmeasurable neurophysiological variables. This will blaze a new field for understanding brain function and will have implications for monitoring and controlling the brain with medical devices and imaging brain activity in new and important ways.


Required knowledge

Statistical signal processing, Statistical Inference, Machine learning, Deep Learning, Dynamical systems theory or knowledge of some of the above and willingness to learn other fields. Must have Python, R or Matlab programming experience.


Project funding

Project based scholarship


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