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Two positions in machine learning in cognitive neuroscience

last modified Mar 05, 2018 05:01 PM
2 positions (Post-doctoral fellowship and PhD studentship) are available to work at the Adaptive Brain Lab, University of Cambridge, UK.

Work in the lab aims to understand how humans of all ages translate sensory experience into complex decisions and adaptive behaviours. 

Projects will focus on machine learning applications in neuroscience. We aim to develop predictive models that synthesise multivariate data (high-field brain imaging and behaviour) to understand the mechanisms that mediate individual ability for learning and brain plasticity.

Applicants should have a degree in a relevant area (e.g., Neuroscience, Mathematics, Engineering, Computer Science, Physics). Programming skills are essential and experience with computational modelling and/or brain imaging preferable.

Please apply online: 

Post-doctoral fellowship:

PhD studentship:

Please direct Informal enquiries to Prof. Zoe Kourtzi (

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New paper in Nature Human Behaviour!

Jan 15, 2019

A new publication by Dr. Vasilis Karlaftis, Joseph Giorgio, Dr. Andrew Welchman and Professor Zoe Kourtzi combines behavioural modelling with functional and structural brain connectivity and shows that individuals learn the structure of variable environments by employing alternate decision strategies that engage distinct brain networks:

New paper in e-Neuro!

Jan 08, 2019

A new publication by Dr. Vasilis Karlaftis, Dr. Andrew Welchman and Professor Zoe Kourtzi answers how we extract meaningful structure and make predictions in novel environments.

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