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for scaling new models of care. The course explores how data and AI coordinate people, processes, and technology to support behavior change, precision care pathways, and continuous service improvement. Case
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not required): Experience with ML-based tools for image-analysis and signal processing, development of ML prediction tools Experience with PyTorch and/or TensorFlow, experience with databases and high
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technology development are deeply valued. Applicants must have earned a PhD in a relevant field with a clearly demonstrated record of excellence in research and teaching. We are particularly interested in
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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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the field. Students will engage with industry partners, and work through a process that results in a functional prototype. The resulting designs are assessed on their engineering quality and design
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Course description: Praxis III is the capstone course of the Engineering Science Foundation Design sequence and challenges students to apply the models of engineering design, communication, teamwork
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, and document appropriate engineering design opportunities; in the second half they design, prototype, and present engineering designs to a subset of those identified opportunities. In support of
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 months ago
objects come to have meanings. How we recognize and fail to recognize such meanings. The nature, systems, and processes of interpretation. The role of mental models. September 1 to December 31, 2025 (actual
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researchers whose proposed research program aligns with one or more of the Government of Canada’s Science, Technology and Innovation priority areas . Canada Excellence Research Chairs are appointed for eight