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Nature Careers | Northern British Columbia Fort Nelson, British Columbia | Canada | about 1 month ago
Physiological Sciences and the Department of Mathematics at The University of British Columbia (UBC) invite applications for a Tier 2 Canada Research Chair in Mathematical and Computational Modelling in Cell
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | about 16 hours ago
Columbia V6T 1Z2, Canada [map ] Subject Area: Mathematical and Computational Modelling in Cell Biology and Physiology Salary Range: $CAD 150,000-170,000 Appl Deadline: 2025/09/15 11:59PM (posted 2025/07/09
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Academic Job Category Faculty Bargaining Job Title Tier 2 Canada Research Chair in Mathematical and Computational Modelling in Cell Biology and Physiology Department Department of Cellular and
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Vision Group (PVG) at McGill University and Mila—Quebec Artificial Intelligence Institute, led by Prof. Tal Arbel, seeks Postdoctoral Fellows to advance causal-temporal and probabilistic modeling, 3D
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Academic Job Category Faculty Non Bargaining Job Title Research Associate - Pest risk modeler Department Research | Carroll Lab | Department of Forest and Conservation Sciences | Faculty of Forestry
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on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected to develop deep learning models for analyzing whole-slide histopathology
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engineering or computer science - Coding in python, medical imaging models, AI foundation models - 2-4 years experience in similar field - strong foundation in deep learning is essential - Strong analytic and
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asset. Experience with cost-recovery budgeting or entrepreneurial program models is preferred. Skills: Excellent communication skills (oral and written) in English; bilingualism in French is necessary
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University of Toronto Faculty of Information Sessional Lecturer Fall Term 2025 (September - December) INF1343H – Data Modeling and Database Design Course Description: The purpose of this course is
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deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects include modeling of bulk and single-cell