The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a theory proposed by Urbanczik & Senn (2014, Neuron) suggesting that plasticity is driven by prediction errors generated within neurons when the activity in dendrites does not match the activity in the soma.

 

The post holder will work as a part of an interdisciplinary team including experimental neuroscientists studying learning in brain networks in Oxford, as well as other theoretical neuroscientists modelling learning processes in Oxford and Imperial College London. The post holder will also be a member of a research group of Professor Rafal Bogacz, and based in the MRC Brain Network Dynamics Unit, which includes an interdisciplinary community of neurobiologists, engineers and computational scientists.

 

Please see the below 'Job Description' for further details on the responsibilities and selection criteria, as well as further information about the university and how to apply.