Postdoctoral position in AI, epidemiology and health inequalities Full-time

Postdoctoral Position In Ai, Epidemiology And Health Inequalities

Are you interested in working with AI, epidemiology, and health inequalities, with the support of competent and friendly colleagues in an international research environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a postdoctoral position at Uppsala University.

The position is based the research group Molecular Epidemiology at the Department of Medical Sciences, Uppsala University. The workplace will be at EpiHubben, an interdisciplinary research environment that brings together researchers working with large-scale health and socioeconomic data. We offer access to relevant expertise, infrastructure, and support for register-based and computational research. The position provides opportunities to work in close collaboration with Nordic and Baltic research partners within an international consortium. The working language is English.

The postdoctoral position is funded through the NordForsk-funded Nordic–Baltic research project “Ethical and computational evaluation of fairness in AI models for personalized disease prevention across >23 million individuals (fAIrHEALTH)”.

The project investigates fairness and bias in AI-based disease prediction models using nationwide linked health and socioeconomic register data from Sweden, Denmark, Finland, and Estonia. The overall aim is to understand whether advanced prediction models perform equally well across social groups, and how potential inequalities can be identified, interpreted, and mitigated.

Duties: You will primarily work with Swedish nationwide health and socioeconomic register data, in close collaboration with Nordic and Baltic partners. The duties include:

• contribution to the study design for preparation and evaluation of AI-based prediction models
• execution and interpretation of disease risk prediction and algorithmic fairness across demographic and socioeconomic groups
• contribution to scientific publications and presentations within an international research consortium

While interest in computational methods is important, the position is particularly suited for you that have strong expertise in epidemiology, population health, and health inequalities, with a focus on interpretation of complex data, rather than purely technical machine learning development.

The work will be supervised by Professor Tove Fall and Dr Hannah Brooke.

Requirements: A PhD degree in epidemiology, public health, biostatistics, or a closely related field, or a foreign degree considered equivalent to a PhD degree. The degree must be obtained by the time the employment decision is made. Preference will be given to applicants who obtained their PhD no more than three years prior to the application deadline. The three-year period is calculated from the application deadline. The period may be extended due to special circumstances such as sick leave, parental leave, or duties within labour unions.

In addition, the applicant must have:

• strong understanding of epidemiological methods and observational study design
• experience of independently managing large-scale register data or administrative health data
• excellent quantitative skills and documented experience analysing data using statistical software such as R, Stata, or Python
• interest in methodological questions related to fairness or bias in prediction models
• ability to plan, conduct, and take responsibility for research tasks, both independently and in collaboration
• strong written and oral communication skills in English, with the ability to explain and discuss complex results with researchers from different disciplinary backgrounds
• a structured, thorough, and reliable work ethics, with attention to data quality, documentation, and reproducibility

Additional qualifications:

• experience working with Swedish or Baltic region health registers
• research experience in health inequalities or social determinants of health
• experience working in interdisciplinary research environments
• experience with research on large language models and/or other AI methods
• ability to understand Swedish

About the employment:

The employment is a temporary position of 2 years according to central collective agreement with the possibility of 1 year extension. The position is full time. Starting date according to agreement. Placement is Uppsala.

For further information about the position, please contact: Tove Fall, tove.fall@medsci.uu.se.

Please submit your application by 18th of February 2026 UFV-PA 2026/261.