25 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" uni jobs at THE UNIVERSITY OF HONG KONG
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Experiential Learning team. The appointee will play a key role in designing and delivering innovative, engaging, and high-impact experiential learning opportunities for undergraduate students, with a particular
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Ref.: 534447 Work type: Full-time Department: Teaching and Learning Innovation Centre (47500) Categories: Teaching Staff Lecturer in the Teaching and Learning Innovation Centre (TALIC) (Ref.: 534447
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to staff position within a Research Infrastructure? No Offer Description Ref.: 534447 Work type: Full-time Department: Teaching and Learning Innovation Centre (47500) Categories: Teaching Staff
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. More information about the Faculty can be found at https://web.edu.hku.hk/ . The Positions We now invite applications for appointment as Professor/Associate Professor/Assistant Professor in Learning
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as a research-led comprehensive university through upholding the highest international standards of excellence in its research pursuits, scholarship, teaching and learning, and service to the community
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intelligence and machine learning in mental health, big data analytics, and pharmacoepidemiology. Applicants who adopt multidisciplinary approaches to address key challenges in psychiatry and mental health
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of genomics, transcriptomics, proteomics, and metabolomics data, as well as expertise in molecular docking, virtual drug screening, and the application of deep learning and machine learning algorithms
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Science, Public Policy or a relevant social science discipline with strong quantitative focus. Priority will be given to those with: The ability to teach Machine Learning, Programming (Python-based
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committed to providing high-quality education in Artificial Intelligence (AI) for undergraduate students to keep status quo. These courses represent key initiatives to promote active learning and
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evidenced by positive student feedback; (b) teach across a range of courses; (c) produce, evaluate and revise teaching and learning materials; (d) work on meeting self-identified professional development