[FieldTrip] postdoc positions in computational psychiatry at UCL

Quentin Huys q.huys at ucl.ac.uk
Mon Oct 30 00:29:26 CET 2023


(Apologies for cross-posting)

We are delighted to announce postdoctoral positions available at the UCL Applied
Computational Psychiatry Lab (www.acplab.org, PI Quentin Huys).

The RELMED project is an exciting computational psychiatry study that will
combine cutting-edge computational methods with two large three-arm randomized
clinical trials to test whether different antidepressants treat depression via
different reinforcement learning mechanisms.

The main outcomes are behaviour and EEG. So we are seeking experts in EITHER
cognitive/RL task design and analysis, OR design and analysis of RL tasks for
EEG. This will be a team, open-science effort, extensively involving lived
experience experts and the wider research community.

Researchers will work with a broad array of expert PIs including including
Michael Browning (Oxford), Ray Dolan (UCL), David Kessler (Bristol), Neil Nixon
(Nottingham), Richard Morriss (Nottingham), Stuart Watson (Newcastle) and Nicola
Wiles (Bristol), and an extensive network of collaborators including Isabel
Berwian (Princeton), Roshan Cools (Donders), Peter Dayan (Max Planck Tuebingen),
Michael Frank (Brown), Nathaniel Daw (Princeton), Catherine Harmer (Oxford), Rob
Howard (UCL), Yael Niv (Princeton), Diego Pizzagalli (Harvard), Argyris
Stringaris (UCL) and others.

The positions should be excellent career opportunities, with outstanding
networking possibilities, the ability to gain experience across clinical,
lived-experience, computational, pharmacological, neuroimaging and open-science
domains, and to answer societally important questions

The Applied Computational Psychiatry lab is situated within the UCL Max Planck
Centre for Computational Psychiatry and Ageing Research and the Division of
Psychiatry at UCL.

Official job advertisement is here:
https://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?nPostingId=7266&nPostingTargetId=16639&id=Q1KFK026203F3VBQBLO8M8M07&LG=UK&languageSelect=UK&mask=ext



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