Postdoctoral Researcher on Cognitive Neuroscience Data Modelling of Brain Dopamine Function

As a postdoctoral researcher, you will be part of the HBP-funded project 'Building a prediction model of dopamine drug effects on human brain and cognition'. Dopamine is implicated in healthy brain function and brain disorders, and many disorders are routinely treated with dopaminergic drugs. Yet there is huge variability in dopaminergic drug effects both within and across individuals. This provides a major problem for psychiatry, where the therapeutic drugs that are prescribed improve behaviour and cognition in some patients, while not being effective or even impairing behaviour and cognition in others.
You will be responsible for integrating existing pharmacological task-related fMRI, dopamine PET, cognitive-behavioural, physiological and subjective report data to build a prediction model of dopamine drug effects on human brain and cognition. To this end, you will develop and optimise next-generation statistical (machine learning) tools that allow constraints based on (i) computational models of behaviour (reinforcement learning and decision making), (ii) probabilistic cytoarchitectonic brain maps of the dopaminergic midbrain nuclei (SN, VTA), and catecholamine receptor maps, and (iii) population-based normative models of individual variation in task-related brain activity, developed using other multi-modal neuroimaging datasets from large cohorts. The multiple variables will be linked using purpose-built multivariate regression techniques similar to canonical correlation analysis (CCA), which will allow us to encode mechanistic knowledge in the model, enabling the testing of precise hypotheses about dopamine function across individuals, thereby advancing beyond the purely data driven nature of classical CCA.

You will be expected to play an active, inspirational role in the campus-wide Computational Psychiatry initiative that spans faculties and institutes across campus.