Víctor M. Pérez García

MOLAB (Mathematical Oncology Laboratory) is inviting expressions of interest from outstanding early-career PhD holders for upcoming postdoctoral fellowship opportunities in mathematical oncology , applied mathematics , machine learning , and cancer biology . The group develops mechanistic mathematical models and digital twins for clinically relevant problems in cancer research. Their work combines mathematical modelling, biomedical data analysis, medical imaging, machine learning, and close collaboration with clinicians and experimental scientists to advance personalized oncology. Current research themes include modelling of brain tumors and brain metastases, immunotherapy, radiopharmaceutical therapies, cancer metabolism, treatment optimization, mechanistic machine learning, and digital twins for precision medicine. They are particularly interested in candidates with a strong publication record and expertise in one or more of the following: mathematical modelling and dynamical systems, applied mathematics and scientific computing, machine learning and artificial intelligence, medical image analysis, computational biology and systems biology, and data science for biomedical applications. Researchers may be considered for competitive fellowship schemes such as Juan de la Cierva , Ramón y Cajal , and other national or regional funding programmes. The post encourages early contact so the group can identify suitable projects and funding opportunities and prepare competitive applications together. Interested candidates should contact Prof. Víctor M. Pérez García at [email protected] or another group professor. Applicants should send a CV with publications, a brief statement of research interests and career goals, a copy of the PhD certificate or expected completion date, and contact details for two academic referees. This opportunity is based in Spain and is aimed at researchers worldwide who want to build an independent research profile at the interface of mathematics, AI, and oncology.