A postdoctoral position is available to make a leading contribution to an ERC-funded project “Dynamic network reconstruction of human perceptual and reward learning via multimodal data fusion”, working with Prof Marios Philiastides.
The work aims to develop a unified framework for integrating perceptual and reward learning and understand the extent to which they share a common computational and neurobiological basis. The job has a strong theoretical neuroscience component and requires the development of computational models to uncover and predict patterns in large multimodal datasets [e.g. behaviour, simultaneous EEG-fMRI and eye-tracking data].
Moreover, the work will focus on the development of a computational framework, in which neural data can be used directly to constrain parameter estimation [i.e. neurally-informed cognitive modelling] to enable mechanistic insights that might otherwise be missed with a conventional modelling approach [i.e. based on behaviour alone]. The post-holder will also be contributing to the design and programming of experiments, recruiting and running the participants.
Closing date: 11th May 2021