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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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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
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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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. They also present challenges: New types of data, (e.g., from DNA testing) may increase risk to privacy. For machine learning and artificial intelligence to work properly, data needs to be centralized
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us: Student Life connects life to learning. We believe every student should have the opportunity to participate in university life actively and find connection and community while discovering new ways
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applications of machine learning for textual transcription; specialist imaging techniques including multi-spectral imaging and micro-CT scanning; the mediation and digitization of social processes; artistic and
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communicate with both technical and non-technical audiences, as well as collaborate with cross-functional teams. Assets (Nonessential): Understanding of machine learning capabilities. Experience with ETL
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residences include Chestnut Residence, Oak House, Graduate House, and Knox Residence. We strive to offer a supportive and dynamic living-learning environment for students that fosters academic success
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of lifelong learning. Building on the momentum of learners’ success, the School has earned a global reputation for innovative leadership in continuing education. Position Summary Reporting to the Dean