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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 months ago
collegial learning and working environment Excellent written and oral communication skills Strong presentation and public speaking skills Strong computer skills, including Microsoft Office Broad knowledge
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, excellence, gratitude, accountability, learning and intentionality. Your opportunity: Work where the world comes to think, discover and learn. As an important member of the Temerty Faculty of Medicine Office
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Equity, Diversity and Inclusion (EDI) Office develops and implements initiatives aimed at advancing equity, diversity and inclusion within the learning and working environments across the Faculty of Arts
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, experiential learning and the role of legal education and law student volunteerism; and engaging in profile-raising activities. QUALIFICATIONS: Undergraduate university degree and law degree (LL.B. or J.D
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the needs of the University of Toronto community and aims to create exceptional environments for learning and life-long memories while generating a sustainable source of revenue for the University by
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 months ago
range of topics, such as Software Engineering, Machine Learning and Data Mining, Quantitative Finance, Mathematics, and Applied Statistics. Our programs are in high demand and attract a large number of
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the role that libraries, librarians, books, and the publishing industry have played during and in the aftermath of regional and global political and military conflicts. Through a specific investigation of
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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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that projects achieve the security goals and controls of MedIT. Essential Qualifications University degree in technology-related discipline including but not limited to Computer Science, Computer Engineering or
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include AI-driven metadata management, machine learning applications in cataloging and discovery, and the ethical concerns surrounding bias, privacy, and surveillance in AI systems. The course will also