PhD Opportunities

The PhD candidate will lead the computational and theoretical track of an interdisciplinary smart-materials project, using coarse-grained and atomistic simulations and machine-learning surrogate models to screen MOF-peptide combinations and connect molecular mechanisms with experimental validation. The appointment is 38 hours per week, initially 18 months and extendable after satisfactory evaluation to a total of four years, with a preferred start near the end of 2026. The project includes research collaboration with TNO and is subject to the university's stated knowledge-security screening because of its security-sensitive or dual-use context.

Applicants need a master's degree or equivalent in chemistry, physics, computational science, biochemistry, physical chemistry or a closely related field, plus experience with molecular simulations and/or machine-learning techniques, strong C or Python programming skills, and excellent oral and written English and Dutch.