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This course prepares students to deliver health informatics initiatives that create measurable value in real clinical and public health settings. Students learn core and modern project management
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Sessional Lecturer Position Posting Date: October 6, 2025 Program: Executive Master of Health Informatics (eMHI) Sessional Dates of Appointment: Winter 2026, January to April Course Description
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of Computer Science Campus: St. George (Downtown Toronto) Description: The Department of Computer Science in the Faculty of Arts and Science at the University of Toronto invites applications for two full-time teaching
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Technology, the Manager, Information Technology (Research Computing) has the primary responsibility for providing strategic leadership and management for the Faculty’s research computing initiatives, ensuring alignment
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 24 days ago
: Department of Mathematical and Computational Sciences Campus: University of Toronto Mississauga (UTM) Description: The Department of Mathematical and Computational Sciences at the University of Toronto
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research and designing pedagogical resources, initiatives and approaches. The Computation and Data Science Education (CDSE) initiative aims to catalyze and support the integration of computation and data
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candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include
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candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include
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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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, this candidate will align computational methods with experimental workflows. The focus will be on developing advanced machine learning algorithms for monitoring various in vitro cell culture models (2D, 3D