Postdoctoral Researcher (Machine Learning for Multimodal Healthcare AI)

Postdoctoral Researcher in Machine Learning for multimodal healthcare AI to build deep learning, multimodal fusion, and longitudinal models on clinical data (structured labs, imaging, pathology, and multi-omics). Responsibilities include designing and deploying foundation-model-inspired pipelines for patient trajectory modeling and treatment simulations, integrating diverse health-system data, developing clinician-facing software tools, co-leading translational AI research with clinicians and data scientists, and contributing to publications and grant proposals. The role involves data preprocessing, model development (causal inference, time-aware architectures, generative/predictive models), deployment within UHN’s digital ecosystem, mentorship of junior researchers, and staying current with state-of-the-art ML in medicine. Requires a PhD (or imminent), strong Python skills, and experience with PyTorch/TensorFlow, with interest in multimodal learning and healthcare applications.