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At a glance
- Tools mentioned
- Python
- Degree background
- Master’s degree (or equivalent) in chemistry, physics, computational science, biochemistry, physical chemistry or a closely related field.
- Project focus
- Build surrogate models and apply machine learning techniques to extract design rules and rapidly screen thousands of MOF-peptide combinations, prioritizing the most promising systems for detailed simulation and experiment.
PhD position at University of Amsterdam: key facts
- Opportunity type
- PhD position
- Organization
- University of Amsterdam
- Location
- Amsterdam, Netherlands
- Field / discipline
- Artificial Intelligence, Chemistry
- Application deadline
- 15 Oct 2026
- Funding / compensation
- Paid
- Duration
- See source description
- Last source check
- No source check recorded
About this phd position at University of Amsterdam
- Use coarse-grained and atomistic simulations to understand the interactions between peptides and surfaces, including MOFs, and unravel the physical mechanisms of their aggregation at these surfaces.
- Build a highly coarse-grained model for MOFs with tunable pore and surface chemistry and study the physicochemical properties of peptides loaded into the materials.
- Build surrogate models and apply machine learning techniques to extract design rules and rapidly screen thousands of MOF-peptide combinations, prioritizing the most promising systems for detailed simulation and experiment.
- Closely collaborate with your experimental colleague to link computational and experimental results.
- Contribute to the validation of the experiments at TNO, publish and present your results, contribute to the supervision of BSc/MSc students
- Publish and present your work within the project consortium and on international scientific platforms
- Contribute to the teaching activities of the department.
- Master’s degree (or equivalent) in chemistry, physics, computational science, biochemistry, physical chemistry or a closely related field.
- Demonstrated experience with molecular simulations (coarse-grained and atomistic) and/or experience with machine learning techniques (e.g. VAE, UMAP, surrogate models).
- Working carefully and reproducibly, document simulation conditions and results clearly, and are motivated to analyse complex data and connect these results to experimental results.
- Excellent programming skills (e.g. C, Python).
- Excellent communication skills in oral and written English and Dutch.
- Strong initiative and excellent time management skills.
- Open to collaborate with students (BSc/MSc), PhDs and PDs involved in related project and research groups within and outside the Netherlands.
- 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
- multiple courses to follow from our Teaching and Learning Centre;
- multiple courses on topics such as leadership for academic staff;
- multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
- 7 weeks birth leave (partner leave) with 100% salary;
- partly paid parental leave;
- the possibility to set up a workplace at home;
- a pension at ABP for which UvA pays two third part of the contribution;
- the possibility to follow courses to learn Dutch;
- A motivation letter (max. 1 pages A4)
- Your CV, including the months (not just years) when referring to your education and work experience, including a list of publications
- Contact details of at least one academic reference
Research labs in Artificial Intelligence, Chemistry at University of Amsterdam
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Source and listing information
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