Topic: generative modelling

Develop generative modelling methods, scalable training algorithms and foundation-model technologies in Charlotte Bunne’s Artificial Intelligence in Molecular Medicine Lab. Research directions include diffusion and flow models, multimodal representation learning, efficient adaptation and AI for scientific discovery. The appointment provides dedicated access to CSCS and Swiss AI Initiative computing. Biomedical experience is not required. The preferred start is autumn 2026, with later dates by arrangement.

Max Welling discusses how ideas from physics may inform the next generation of artificial intelligence. The conversation examines physical structure, generative modelling and the relationship between learning systems and scientific discovery.

Archive listing for the EMBO | EMBL Symposium held on 10–13 March 2026 at EMBL Heidelberg and online. The meeting connected researchers applying artificial intelligence to sequencing, imaging and structural biology. Programme themes included foundation models, learning across data types, interpretability, generative modelling and translating algorithms into biological insight. The official event page retains the programme and speaker information. This event has ended; registration and abstract submission are closed.