Postdoctoral Scholar – Deep Learning for Protein Design

Develop deep-learning methods for generative protein design at the interface of machine learning, molecular simulation, structural biology and experimental protein engineering. Projects can investigate conformational ensembles, integrate protein language models with physics, or design proteins for challenging membrane and sugar interfaces. The researcher can develop an independent direction while collaborating with computational and experimental colleagues. Applicants submit a CV, research-interest statement and three referee contacts to the laboratory contact listed on its recruitment page.

PhD or equivalent in computer science, computational biology, bioinformatics or a related field, with experience in generative modelling, structure prediction, protein language models or PyTorch. Strong candidates from adjacent quantitative fields are encouraged. Experimental protein-characterisation experience is not required. Applications are reviewed on a rolling basis until the role is filled.