64 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Canada
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-generation smart factories. The candidate's technical skill set must seamlessly bridge: Control Theory and System Dynamics Machine Learning, Sensor Technology and Data Analytics, Mechanical/Electromechanical
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of an Indigenous language, which includes using a computer. Focus is on nouns, verbs, prefixes, and suffixes, along with specific Indigenous lexicon. Posting Dates: March 04 - 10, 2026 Application Deadline: March 10
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 20 hours ago
, and teaching mode see the University of Toronto, Timetable Builder at: https://ttb.utoronto.ca/ . Faculty/Division: University of Toronto Mississauga. Department/Subject Area: Communication, Culture
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a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve
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overall quality of life is outstanding. McGill University, founded in 1821, is one of Canada’s best-known institutions of higher learning and is consistently ranked among the top 20 public universities in
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and revise existing IMAGE machine‑learning components to optimize efficiency, scalability, and quality of results. Implement conversions of existing non‑LLM components to LLM‑based approaches where
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on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day. The Department of Electrical and Computer Engineering has
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that incorporate artificial intelligence and machine learning or climate change and human health are of particular interest. BWF believes that a diverse scientific workforce is essential to the process and
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning
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. Integration of Artificial Intelligence and Remote Sensing Science: machine-learning / automated analysis of large datasets, calibration and validation, feature extraction, image processing and classification