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: Edward S. Rogers Sr. Department of Electrical and Computer Engineering Campus: St. George (Downtown Toronto) Description: The Edward S. Rogers Sr. Department of Electrical and Computer Engineering (ECE) in
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University of Toronto Faculty of Information Sessional Lecturer Winter Term 2026 (January - April) INF351H1 – Information Design Studio I: How to Make a Computer and Why Course Description: By
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 4 days ago
relationships by finding individuals with strong professional office skills and work ethic. UTM I&ITS is a modern service delivery operation, processing tens of thousands of incident, change, and service requests
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 5 hours ago
, applied tools used to scale applications on the desktop and in the cloud. Topics include caching, load balancing, parallel computing and models of computation, redundancy, failover strategies, use of GPUs
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bioinformatics, essential elements of protein and enzyme structure and function, biomembranes, and membrane proteins, metabolism of carbohydrates, lipids and proteins, and molecular and cell biology. Estimated
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processing, development of ML prediction tools Experience with PyTorch and/or TensorFlow, experience with databases and high-content imaging platforms Familiarity with generative modeling Experience with
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chemistry, with experience planning and troubleshooting synthetic routes and performing parallel library synthesis. The ideal candidate should have experiences with one or more of the following: working with
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 2 months ago
the logistical execution of events and programs, developing communication strategies, evaluating outcomes, and coordinating internal funding competitions. In parallel, the Advisor serves as a key resource on
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interpreting raw data streams from radio telescopes or similar data Experience in high performance computing, especially involving massively parallel applications Experience with cluster computing and job
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maintenance Experience in interpreting raw data streams from radio telescopes or similar data Experience in high performance computing, especially involving massively parallel applications Experience with