Postdoc in Statistical Genetics Casale Group
Pubblicato il 02-10-2026 - Human Technopole in Milano
Build the science that shapes the future of human health.
Build the science that shapes the future of human health. Application closing date: 04.11.2026 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 Casale Group in the Health Data Science Centre develops AI methods that transform population-scale human data into mechanistic models of disease. Our research integrates large-scale human genetics with molecular and clinical data to generate testable hypotheses that accelerate biological discovery and therapeutic innovation.
Your mission
As Postdoc in Statistical Genetics, you will develop computational methods that connect human genetic variation to biological function. Using population-scale human genetics together with single-cell, spatial, and multimodal molecular data,
you will identify the cells, cellular states, and biological programs through which genetic variation influences disease. Your work will sit at the intersection of statistical genetics, machine learning, and mechanistic biology, with opportunities to lead methodological innovation and drive high-impact biological discoveries. The role will give you access to population-scale human genetics, rich multimodal molecular and clinical datasets, and world-class AI and experimental research environments. This combination provides a unique foundation for ambitious research and enables biological questions to be explored at unprecedented scale. As part of Human Technopole's interdisciplinary AI ecosystem, you will engage closely with the European AI community, including through collaborations with Helmholtz Munich and connections to the ELLIS network. Your work will agevolazioni from interactions with computational, biologica