AI Scientist
Pubblicato il 21-10-2026 - Human Technopole in Milano
Build the science that shapes the future of human health. Application closing date:
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.
We are recruiting an ambitious (Senior) AI Scientist to build the reusable AI foundations and agentic scientific systems that power the group’s research across human genetics, multimodal biology, and disease. Your mission As (Senior) AI Scientist, you will develop next-generation AI systems at the interface of ambitious biological research and frontier artificial intelligence, using population-scale genetics and multimodal biomedical data to uncover mechanisms of human disease.
You will turn methods and models emerging from this research into robust, reusable AI capabilities—including foundation models, multimodal representation learning, agentic workflows, evaluation frameworks, and scalable research software—that can accelerate discovery across multiple projects.
A longer-term goal is to develop AI systems that increasingly act as scientific collaborators: connecting evidence across biological scales, proposing testable hypotheses, identifying informative analyses, and working alongside researchers to accelerate iterative cycles of biological discovery.
Your work will combine methodological innovation, biological discovery, and scientific software development at the intersection of artificial intelligence, computational biology, and human genetics. You will have substantial scientific and technical ownership, with the opportunity to help shape the group’s technical AI architecture while leading and contributing to high-impact scientific publications, open-source software, and reusable research capabilities.
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 vantaggi from interactions with computational, biological, and clinical groups across the institute, alongside opportunities for international collaboration, research exchanges, interdisciplinary training, and engagement with industry.
You will also draw on the group’s established network across leading academic institutions and industry partners in Europe and North America, helping you build collaborations, broaden your expertise, and accelerate the impact of your research.
Grow your skills What you'll bring Essential PhD in Machine Learning, Artificial Intelligence, Computer Science, Computational Biology, or a related quantitative discipline,
or expected completion within the next six months. At least 4 years of relevant research experience by the start of the position, including doctoral research.
Strong track record of scientific output in AI, machine learning, computational biology, or biomedicine, demonstrating independent methodological or technical contributions through publications, open-source software, models, or comparable research outputs.
Excellent programming and software engineering skills in Python, with experience building scalable and maintainable research software, model-training workflows, or AI systems.
Strong expertise in modern machine learning and AI, with demonstrated ability to design, develop, and critically evaluate advanced methods for challenging research problems.
Experience with modern software engineering and computational research practices, including version control, testing, documentation, reproducibility, and large-scale GPU or HPC environments.
Preferred Industry or applied R&D; experience in roles such as AI/ML architect, research scientist, machine learning scientist, or equivalent positions with substantial technical ownership.
Experience developing foundation models or other large-scale AI systems for scientific or biomedical applications.
Experience developing or applying LLM-based agents and agentic workflows for scientific or technical tasks, including analysis, information integration, automation, or hypothesis generation.
Experience integrating multimodal biomedical datasets, including molecular, imaging, clinical, or population-scale data.
Experience leading collaborative software projects and contributing to open-source scientific software or models.
Experience with workflow management, containerisation, and scalable GPU/HPC com