36 information-humanities-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in Canada
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at McGill University is recruiting a fully funded Postdoctoral Fellow to lead projects at the intersection of human genetics, proteomics, and multi-omics for drug target discovery and precision medicine in
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Position Description The laboratory of Dr. Arielle Elkrief, MD, Co-Director of the CHUM Microbiome Centre, is seeking a highly motivated Postdoctoral Fellow to join a multidisciplinary research
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Learning (SCSIL) is seeking a highly motivated Postdoctoral Researcher with training in computer science, artificial intelligence, biomedical engineering, or a closely related field to join an
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Identification of Undiagnosed and Misdiagnosed hEDS/HSD Cases Position summary The Canada Excellence Research Chair (CERC) in Genomic Medicine at McGill University is seeking a highly motivated Postdoctoral
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to James McKay, Indigenous HR Lead at [email protected] . Toronto Metropolitan University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA), and aims to ensure
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The Gerald Bronfman Department of Oncology (GBDO) is seeking a highly motivated Postdoctoral Researcher to contribute to leading-edge research evaluating cancer care delivery, quality of care, and patient
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McGill University | North Peel Regional Municipality Kleinburg, Ontario | Canada | about 1 month ago
of health and medicine This position is unionized, and the incumbent will hold dual status as both a student and a McGill employee, and as a member of the AMURE (Postdocs) bargaining unit. For interested
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novel molecular mechanisms associated with trauma which may reflect clinicopathology and/or serve as potential biomarkers. This position will involve studies using human brain tissue, mouse models, and
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innovation and scholarship of tomorrow to develop the skills to build world-class research and drive Canadian prosperity and competitiveness. Description The CPRA program is a federal research talent
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convection. The objective is to develop reduced but realistic models of cumulus life cycles that may be applied toward cumulus parameterization and/or machine-learning algorithms for predicting short-term