PhD in Epidemiology on value-of-information methods for validating clinical prediction models and AI Maastricht University in Netherlands

Maastricht University is advertising a PhD in Epidemiology focused on value-of-information methods for validating clinical prediction models and AI. The project asks a practical and important question in modern epidemiology and health data science: when is an AI model truly ready for clinical use, and when is more evidence still needed?

The research will develop methods that translate uncertainty into clinically meaningful consequences, such as the expected number of misdiagnoses. It also includes methodological work at the intersection of statistics, health economics, simulation studies, and software development, including user-friendly tools such as an R package.

The position is based in the Department of Epidemiology at Maastricht University and is part of a VIDI-funded team led by Dr Laure Wynants, alongside other PhD and postdoctoral researchers. The post is full-time and starts with a 12-month contract, followed by a possible 3-year extension after positive evaluation.

Ideal candidates will have strong interests in model validation, clinical epidemiology, methodological statistics, responsible AI, and health data science. The post is especially relevant for applicants interested in trustworthy AI in medicine, decision support, and evidence-based evaluation of prediction models across hospitals, populations, and clinical settings.

The application deadline is 21 April 2026. Interested candidates should apply via the Maastricht University vacancies page and review the full vacancy for any required documents and eligibility details.