Canada Impact+ Emerging Leader in Computational Oncology
Core
Develop and lead an independent research program in computational oncology using quantitative and machine-learning methods to study cancer evolution, therapy resistance, and immune escape in urologic cancers.
Role type
Assistant Professor / Senior Research Scientist (Early Career Researcher)
Builds
Production ML models | research | client delivery (translational science)
Domain
Healthcare + Computational Biology / Bioinformatics
Deliverable
production ML models | research
Required skills
quantitative modelling of cancer evolution, single-cell genomics, artificial intelligence, causal machine learning, computational modelling, single-cell multi-omics, Bayesian generative models, phylogenetic inference, multimodal data integration, software engineering
Preferred skills
probabilistic modeling, causal machine learning, phylogenetic and evolutionary inference, clonal dynamics, immune-tumour interactions, uncertainty quantification
Technologies
single-cell genomics, spatial profiling, multi-omics datasets, Bayesian generative models, phylogenetic inference tools
Responsibilities
Develop and lead independent research program, translate computational findings into testable hypotheses and biomarkers, participate in teaching activities, provide mentorship to learners, provide service to the University
Seniority
Early Career (Assistant Professor)
