The MRC Brain Network Dynamics Unit provides an exceptional training and mentoring environment for students, postdoctoral researchers, support staff, academic clinicians and visiting scientists at all career levels and from all over the world. The MRC BNDU is an outward-looking and international community.
Closing Date

We have an exciting opportunity for a Postdoctoral Researcher in Computational Neuroscience to join the MRC Brain Network Dynamics Unit within the Nuffield Department of Clinical Neurosciences. The postdoctoral researcher will work within an interdisciplinary team investigating how the neural circuits in the brain represent, use and learn the information about the costs and benefits of alternative choices during decision making.

The post holder will develop computational models of learning and decision making in neural circuits that will provide a framework to generate precise predictions and interpret experimental data. They will work on a project aiming to uncover the function of important neural pathways, known as the direct and indirect pathways of the basal ganglia. The post-holder will closely work with another postdoctoral researcher, who performs experiments using techniques such as in vivo photometry during sophisticated behavioural tasks.

It is essential that the post-holder hold, or be nearing completion of, a Ph.D. or equivalent qualification in a relevant area and have expertise in mathematical modelling and data analysis. They also need to have proficiency in programming and a demonstrable record of originality, creativity and productivity in research, including first-author publications. It would be beneficial if they also have experience in computation models of reinforcement learning or decision making.

The post is full-time for a fixed-term until 31st December 2022 in the first instance.

Only applications received before 12.00 midday on 22nd October 2020 will be considered.

More details, including instructions on how to apply, can be found on the University of Oxford's online recruitment system (Vacancy ID 144425).

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