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.
Three-year, full-time doctoral research position applying language-model interpretability to protein function. The computational project will study how protein language models represent biological properties, build immunogenicity classifiers and help steer protein generation, in collaboration with experimental researchers. The role is funded at TV-L E13 and preferably starts in January 2027. Applications are requested by 15 October 2026, after which the vacancy explicitly remains open until filled.