Two post doctoral Research Associate/Assistant positions in Learning and Brain Plasticity are available to work at the Adaptive Brain Lab (http://www.abg.psychol.cam.ac.uk).
The first position will focus on behavioural and brain imaging studies that will combine high-field (7T) imaging and MEG for investigating the neural mechanisms that mediate learning and brain plasticity in young and older adults. Further interventional approaches (TMS, neuropharmacology) will be employed to test brain connectivity.
The second position will focus on advanced computational modelling of behavioural and multimodal brain imaging data including Bayesian modelling and machine learning approaches.
Research in the lab aims to understand how humans of all ages translate sensory experience into complex decisions and adaptive behaviours by taking into account previous experience and learning. We address this challenge using an interdisciplinary approach that combines behavioural paradigms, movement recording, multimodal brain imaging (MRI, EEG, MEG, TMS) and state-of-the-art computational methods. We apply these techniques to study the young and ageing brain and understand adaptive behaviours across the lifespan.
Applicants should have or be close to obtaining a PhD, and have a strong academic track record, in a relevant area (e.g., Neuroscience, Psychology, Mathematics, Engineering, Computer Science, Physics). Programming skills are highly desirable and experience with computational modeling and/or brain imaging preferable.
The salary range if appointed as a Post doctoral Research Associate is £29,301 - £38,183 per annum and the salary range if appointed as Research Assistant is £25,298 - £29,301 per annum with promotion to Post doctoral Research Associate on attainment of PhD.
Informal enquiries should be directed to Professor Zoe Kourtzi (firstname.lastname@example.org)
Further details may be downloaded below.
Fixed-term: The funds for this post are available for 12 months in the first instance with possible extension to 3 years.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please quote reference PJ11340 on your application and in any correspondence about this vacancy.
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