We are seeking

creative, motivated and collaborative researchers to develop next-generation AI methods for scientific and biomedical discovery. The posts span two complementary research directions:

AI for experimental science and multimodal scientific data analysis — developing machine learning methods to support experimental design, interpretation and analysis of complex scientific datasets across biomaterials, biosensing, diagnostics and tissue engineering.

AI for autonomous molecular and materials discovery — developing predictive, generative and foundation-model-based AI methods for molecular optimisation, biomaterials engineering, protein and binder design, lipid nanoparticle formulation and materials discovery.

Successful candidates will contribute to one or both of these areas depending on expertise and interests.
The role is highly multidisciplinary and collaborative, involving close collaboration with experimental and ...