Overview
The University of Amsterdam is recruiting a four-year PhD candidate to model smart self-sealing coatings using molecular simulation, multiscale modelling and machine-learning surrogate models for MOF-peptide materials.
Complete research opportunity details
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.
Eligibility requirements
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.
Tips for this phd opportunity
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- Match your research background to the project, laboratory, supervisor and required methods rather than applying only from the title.
- Prepare a focused academic CV, transcripts, publications and research statement or proposal when requested by the official call.
- Confirm funding duration, stipend/salary, tuition coverage, start date and eligibility for international applicants.
- Contact a supervisor before applying only when the official instructions recommend or require it.
Verification notes
Verified on the exact University of Amsterdam vacancy. The source confirms vacancy 15411, Faculty of Science, 38 hours per week, the four-year PhD structure, monthly salary range, computational and machine-learning scope, qualification requirements, and 15 October 2026 closing date. The official page does not expose a trustworthy publication date, so published_at is left null. Repository checks for vacancy 15411 and the intended path found no existing canonical record.
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