Human Technopole
2 months ago
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Postdoc in AI for Biomedicine at Human Technopole Human Technopole in Italy
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Sep 7, 2026
Country
Italy
University
Human Technopole

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About this position
Postdoc in AI for Biomedicine at Human Technopole, Milan (Italy).
The Casale Lab is launching at Human Technopole in September 2026 and is building AI methods that transform population-scale human data into mechanistic models of disease. The postdoctoral project sits at the intersection of machine learning, computational biology, human genetics, and multimodal biomedical data, with possible work spanning imaging, genetics, molecular data, and clinical data.
This role is designed for an ambitious researcher who wants to develop next-generation AI methods for biomedical discovery. The lab highlights access to population-scale human genetics, rich multimodal molecular and clinical datasets, and a strong interdisciplinary environment connected to biology, medicine, and artificial intelligence. Researchers will also benefit from links to the European AI community through Helmholtz Munich and the ELLIS network, plus opportunities for collaboration, exchanges, and training.
Eligibility highlights: a PhD in Machine Learning, Artificial Intelligence, Computational Biology, Computer Science, Bioinformatics, or a related quantitative discipline; a strong publication record in biomedicine or machine learning; excellent Python programming skills; and strong knowledge of modern AI methods such as deep learning, representation learning, foundation models, and multimodal learning. Experience with imaging, single-cell, spatial transcriptomics, electronic health records, PyTorch/JAX, large-scale computing, or human genetics is preferred.
How to apply: formal applications open on 2026-09-07 via the official Human Technopole recruitment portal. Applicants should prepare a CV, motivation letter, and the contact details of two referees. Informal enquiries are welcome in advance by email.
Funding details
Available
What's required
PhD in Machine Learning, Artificial Intelligence, Computational Biology, Computer Science, Bioinformatics, or a related quantitative discipline. Strong publication record in top biomedicine journals or machine learning venues, ideally with work on AI methods motivated by biological or biomedical questions using large molecular, imaging, or clinical datasets. Excellent Python programming skills and experience developing AI systems for large-scale biomedical datasets. Strong understanding of modern machine learning and AI, including deep learning, representation learning, foundation models, and multimodal learning. Preferred: experience with multimodal biomedical data, imaging, single-cell, spatial transcriptomics, electronic health records, modern AI frameworks such as PyTorch or JAX, large-scale computing environments, and human genetics.
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