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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 days ago
computer package will be used. Course Enrolment (Estimated): 120 Number of Positions: 1 TA Support: 50 hrs per tutorial & per semester Sessional Dates of Appointment: July 1, 2026 – Aug 31, 2026 Class
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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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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 days ago
candidate is expected to teach can be found here: https://www.cs.utoronto.ca/~trebla/CSCB09-2025-Summer/ . The successful candidate must demonstrate thorough familiarity with the course material. Previous
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or information technology. The course will cover material that is relevant to health informatics and focus on the understanding of hardware and software systems. We will focus on the proper design and
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Course Description: In Complexity of Clinical Care, the implications and practical application of the outputs of AI and Machine learning are discussed in class, and in select assigned readings. This class
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position in experimental chemistry, with a preference for candidates able to teach in the areas of physical chemistry, inorganic chemistry or organic chemistry. The research area is broadly defined and
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standards across the various academic divisions, as well as supporting postdoctoral fellows. SGS defines and administers University-wide regulations for graduate education. We share responsibility
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 4 days ago
justification process . Applicants must have earned a PhD degree in biology, biomedical sciences, computational biology, AI/machine learning, bioinformatics, or a related area to the subject matter of this search
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to take a lead with industry stakeholders as well as teach in the Soil Science, Environmental Science and Renewable Resource Management degree programs and other associated certificates and degrees within
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experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image