AI Scientist in Oncology
Pubblicato il 09-10-2026 - IFOM in Milano
IFOM, the AIRC Institute of Molecular Oncology in Milan, is seeking a talented AI scientist to develop and apply machine learning and generative AI to one of the central questions in IFOM's long-term strategic plan and one of the hardest problems in oncology: discriminating cancers destined from the onset for indolent behaviour ("born to be good") from those with aggressive behaviour ("born to be bad"), including those featuring early metastasis and resistance or relapse after therapy.
Working within IFOM's institute-wide AI programme and in close collaboration with its experimental and clinical groups, you will use machine learning and generative AI to extract mechanistic insights, biomarkers and therapeutic vulnerabilities from data generated in experimental models and in large clinical cohorts of tumour-infiltrated tissue collected at diagnosis, integrated with clinical annotation of outcome, disease evolution, and response to immunotherapy and personalised treatment, turning IFOM's rich multi-scale data into predictive, mechanistic and clinically meaningful insight.
IFOM is uniquely positioned to tackle this challenging and rewarding question thanks to the convergence of multiple top-notch research activities across the institute's groups.
Role of the AI scientist in the IFOM community
- Apply models that integrate single-cell and spatial omics, genomics, epigenomics, proteomics and multidimensional immunohistochemistry, together with radiomics and pathomics, pharmacogenomic screens in patient-derived xenografts and tumoroids, animal models, and functional genetic screens using CRISPR/Cas9 technologies, to model tumour fate from diagnosis onward.
- Help decode tumour fate from an initial biopsy sample, uncovering determinants of indolent vs aggressive behaviour, including how epigenetic state, dormancy and reawakening, exposure to environmental agents, host immune fitness, and tumour biomechanical properties shape disease trajectory.
- Contribute to trans