Topic: multimodal learning

The Haibe-Kains Lab at Princess Margaret Cancer Centre seeks a researcher for computational oncology, biomarker discovery and treatment-response modelling. Work combines genomic, molecular and clinical data using multimodal learning and foundation models, with reproducible, privacy-aware and federated workflows across collaborating institutions. The temporary full-time appointment lasts two years, with 37.5 hours per week and annual compensation of CAD 54,902–82,352.

Develop machine-learning methods for quantitative neuropathology within the Brain Health initiative. Integrate histology, spatial molecular data, MRI and clinical information to investigate brain-disease mechanisms and progression. The role includes computer-vision models, multimodal learning, Bayesian and causal models, scientific collaboration and open publication of code and models. This grant-dependent position is based in Seattle with hybrid working restricted to Washington State. Annual salary: USD 129,950–162,450. Relocation assistance is offered and visa sponsorship may be available.