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qualifications, the need to acquire experience, previous experience, and previous satisfactory employment under the provisions of this collective agreement. Application Procedure: For detailed information
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scripting methods (i.e. Python, MATLAB, C++, CUDA, Bash, and/or SQL) and machine learning / deep learning methods Active learning, exploration, optimal experiment design, Bayesian optimization, reinforcement
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institutions in regions, countries and cities of strategic priority and leverages international opportunities for research, scholarship, learning and mobility. By providing leadership on international
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machine learning / deep learning methods Active learning, exploration, optimal experiment design, Bayesian optimization, reinforcement learning, and/or representation learning Experience in development and
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catalyst for transformative learning, insights and public engagement, bringing together diverse views and initiatives around a defining purpose: to create value for business and society. We make a
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Sessional Lecturer - CTL7014H - Fundamentals of Teaching and Learning Course number and title: CTL7014H - Fundamentals of Teaching and Learning. Course description: This course will explore
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experience; knowledge of University of Toronto structure; deep familiarity with academic HR life cycle, tenure process, and University academic HR norms. Excellent knowledge of the University’s academic
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the promotion of a respectful and collegial learning and working environment demonstrated through the application materials. The successful candidate will undertake undergraduate and potentially
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. Both courses are connected to an inquiry-based, data driven school-specific Master of Teaching Junior/Intermediate cohort partnered with a TDSB school. As such, one instructor will be hired to teach
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is a catalyst for transformative learning, insights and public engagement, bringing together diverse views and initiatives around a defining purpose: to create value for business and society. We make a