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Human Technopole

Postdoc in Statistical Genetics at Human Technopole Human Technopole in Italy

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Sep 7, 2026

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Country

Italy

University

Human Technopole

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Keywords

Computer Science
Machine Learning
Biostatistics
Biology
Computational Biology
Functional Genomics
Probabilistic Modeling
Medical Science
Causal Inference
Bayesian Statistics
Genetic
Statistics
Bioinformatic
Spatial Transcriptomic

About this position

Postdoc in Statistical Genetics at Human Technopole, Milan, Italy. The Casale Lab is launching at Human Technopole and is building AI methods that transform population-scale human data into mechanistic models of disease. This postdoctoral role sits at the intersection of statistical genetics, machine learning, and mechanistic biology, with a strong emphasis on connecting human genetic variation to biological function.

The successful candidate will work with population-scale human genetics alongside single-cell, spatial, and multimodal molecular data to identify the cells, cellular states, and biological programs through which genetic variation influences disease. The lab highlights opportunities to develop next-generation methods, drive biological discovery across molecular and clinical datasets, and build an internationally recognized research profile through publications and conferences.

Eligibility highlights: a PhD in Statistical Genetics, Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related quantitative discipline; a strong publication record in computational biology/genetics/biomedical journals; excellent Python programming and research software development experience; and strong knowledge of modern AI, including deep learning and representation learning. Preferred experience includes GWAS, biobanks, population-scale genetics, single-cell or spatial transcriptomics, functional genomics, Bayesian statistics, causal inference, probabilistic modelling, and foundation models.

Location: Human Technopole, Milan (Italy). Formal recruitment opens: September 7, 2026. Applications will be submitted through the official Human Technopole recruitment portal and require a CV, motivation letter, and two referees. Informal enquiries are welcomed in advance via [email protected].

Funding details

Available

What's required

Applicants must have a PhD in Statistical Genetics, Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related quantitative discipline. A strong publication record in leading computational biology, genetics, or biomedical journals is expected, ideally with work on computational methods motivated by biological questions using population-scale human genetics or multimodal molecular data. Essential skills include excellent Python programming and experience developing research software for large-scale genomic or molecular datasets, plus strong understanding of modern machine learning and AI, including deep learning and representation learning. Preferred experience includes GWAS, biobanks, population-scale genetics, single-cell or spatial transcriptomics, functional genomics, Bayesian statistics, causal inference, probabilistic modelling, and modern AI architectures/foundation models. Strong analytical thinking, independence, communication, scientific writing, creativity, and collaborative ability are also emphasized.

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