Postdoc
Pubblicato il 13-08-2026 - Human Technopole in Milano
Postdoc doc in health data science | Human Technopole, Milan
Build the science that shapes the future of human health.
Application closing date: 15.08.2026
Join a place where ambitious science thrives
Human Technopole (Milan) is a rapidly expanding life science institute where international researchers and cutting-edge technologies converge to accelerate biomedical discovery. Our mission is to transform bold scientific ideas into advances that improve human health.
Within this mission, the Data Science and Genetic Epidemiology Lab (www.dsgelab.org) develops next-generation AI methods to integrate population-scale healthcare data with human genetics. The team comprises data scientists, biologists, and medical doctors, and is based across two locations: the Institute for Molecular Medicine Finland (University of Helsinki) and Ganna Group - Human Technopole. The lab has a strong track record of high-impact publications.
Your mission
We are seeking an ambitious postdoctoral researcher to help build and deploy population-scale foundation models for electronic health records.
Using real-world patient data from Finland (7 million individuals), Lombardy (10 million), and France (16 million), you will develop AI systems to model disease trajectories, predict healthcare outcomes, and estimate healthcare costs. You will integrate multimodal data, including genetics and -omics, to improve model interpretability and enable causal and counterfactual (“what-if”) analyses.
Your work will sit at the intersection of deep learning, genetic epidemiology, and public health, with opportunities to lead methodological developments and drive high-impact applications, including potential commercial spin-offs.
What Makes This Role Exceptional
You will have access to world-unique resources: complete longitudinal health records covering more than 5 billion medical events, FinnGen with genetics on over 500,000 individuals, and multi-omics profiling (proteomics, single-cell RNA sequenc