Postdoctoral researcher in non‑random selection & causal inference

About the role

The Department of Public Health at the University of Copenhagen seeks a postdoctoral researcher to develop statistical methods for causal inference in studies affected by non‑random participation, especially self‑selection in cohort studies. The position is a three‑year fixed‑term appointment starting 1 October 2026.

Key responsibilities

• Design and implement novel statistical methods to address non‑random selection and attrition in longitudinal cohort data.
• Analyse combined self‑reported questionnaire data and individual‑level Danish national register data.
• Collaborate with the Social Magnifier research group and the SMARTbiomed Causal Inference hub.
• Publish research findings in peer‑reviewed journals and present at international conferences.

Required profile

• PhD in statistics, biostatistics, epidemiology, or a closely related discipline.
• Demonstrated experience with causal inference methods and handling missing or selectively observed data.
• Strong analytical and problem‑solving abilities.
• Ability to work independently and as part of an interdisciplinary research team.

Required skills

• Proficiency in statistical programming languages such as R or Python.
• Experience with causal inference techniques (e.g., propensity scores, instrumental variables, structural models).
• Knowledge of survival analysis and longitudinal data methods.
• Handling large administrative or register datasets.

What we offer

• A three‑year fixed‑term contract with competitive remuneration.
• Access to extensive Danish national register data and a vibrant international research environment.
• Opportunities for collaboration across the Department of Public Health, SMARTbiomed, and external partners.
• Support for publishing and professional development.