Uppsala University’s Department of Information Technology is seeking a PhD student in Multimodal machine learning for precision medicine.
Position description
This PhD project is part of the interdisciplinary WASP-DDLS NEST project AID4BC, which has the overarching aim of advancing data-driven multimodal methods to enable true precision diagnostics throughout the breast cancer pathway. AID4BC’s constellation of partners, located at four leading sites in Sweden, is likely the only constellation globally having access to large (>10,000 patients) matched multimodal data across radiology, pathology and molecular profiling and clinical data.
The focus of this position is on developing methodology for multimodal machine learning, combining large-scale image data with molecular profiling and clinical data. This includes, for instance, research on deep learning-based image analysis and data assimilation methods that update model trajectories over time based on partial, longitudinal, data. The exact details of the project will, however, be decided in a dialogue between the student and supervisor.
The candidate is expected to collaborate extensively with clinical experts at the other sites, with the ultimately goal of uncovering mechanisms underlying breast cancer and translating these insights into precision diagnostics and treatments that improve patient outcomes.
