About the role

Are you a machine learning researcher with expertise in deep generative modelling, eager to apply your methods to some of the most pressing challenges in global health? We are looking for a Research Associate to lead methodological development at the interface of deep learning and infectious disease modelling, working within a highly collaborative international team at Imperial College London.

What you would be doing

You will drive forward methods research in deep generative modelling, simulation-based inference, and neural approaches to spatial and spatiotemporal Bayesian inference. Your work will focus on developing principled, scalable tools, including deep generative modelling and neural surrogate models, that address fundamental computational challenges in fitting complex disease models to data. You will have significant freedom to pursue rigorous methodological innovation, with validation and application grounded in the real scientific problem of antimalarial drug resistance in sub-Saharan Africa.