799 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation" "U.S" positions at University of Toronto in Canada
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galaxy evolution and dark energy. We are dedicated to making our education, training, and activities pleasant and welcoming for all Your opportunity: This is a two-year term position. Under the direction
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 2 months ago
Sessional Lecturer- BIO406H5S: Current Topics in Ecology and Evolution Course description: A combination of lectures and tutorials. The course will emphasize group discussion and critiques
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the universe, such as galaxy evolution and dark energy. We are dedicated to making our education, training, and activities pleasant and welcoming for all Your opportunity: This is a two-year term position. Under
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Sessional Lecturer - CTL1060H - Education and Social Development Course number and title: CTL1060H - Education and Social Development Course description: This course examines the linkages between
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of accessible design guidelines, best practice in Drupal theme development and cross-browser compatibility. Demonstrated skills to simultaneously lead multiple complex projects, with multiple interruptions and
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matters pertaining to the development, maintenance and effectiveness of the core administrative management and student systems at the U of T. Included within these responsibilities are all central SAP
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) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
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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
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, including U.S. student aid programs and government student aid programs from jurisdictions within Canada, along with other financial supports (e.g., loans to students in professional programs), and internal U
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, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for training algorithms. This creates challenges with data security and data flows (due to legislative restrictions). Further, data