Statistical Geneticist

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7hmqiw

Build the science that shapes the future of human health.
Application closing date: 01.09.2026
Join a place where ambitious science thrives
Human Technopole (HT) is an international research institute dedicated to advancing human health through interdisciplinary life science research. Located in Milan's MIND innovation district, HT brings together scientists from around the world to tackle fundamental questions in biology using state-of-the-art technologies and large-scale datasets.

Within this mission, the
Biostatistics Unit
of the
Centre for Genomics – Population and Medical Genomics Programme
provides statistical expertise across research projects, supporting the analysis of complex human genetic and multi-omics data to uncover the biological mechanisms underlying health and disease.

We are seeking a
Statistical Geneticist
to contribute to innovative population and medical genomics research by developing robust analytical strategies and collaborating with multidisciplinary teams with a particular focus on defining and analysing complex multivariate phenotypes,



such as multicellular programmes and multimorbidity measures.

Your mission
As a Statistical Geneticist, you will provide statistical and computational expertise to support cutting-edge genomic research across the Centre.

You Will
- Lead and conduct advanced statistical genetics analyses, including GWAS, polygenic risk scores, fine-mapping, heritability estimation, genetic correlation, Mendelian randomisation, multi-omics integration, and related computational analyses using large-scale genetic, genomic, multi-omic, phenotypic, clinical, imaging, and electronic health record datasets.
- Advise research group leaders, collaborators, PhD students, postdoctoral researchers, and junior analysts on appropriate statistical, genetic, epidemiological, computational, machine-learning, and AI-based approaches to address biological and clinical research questions.
- Translate complex research questions into robust

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7hmqiw