414 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at Nanyang Technological University
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Nanyang Technological University (NTU) has launched the “Care, Serve, Learn” (CSL) initiative as a compulsory, credit-bearing course series for all undergraduates admitted from Academic Year 2025
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the Office of Information, Knowledge and Library Services (OIKLS). Reporting to the University Librarian, this role is about helping shape the future of how students and faculty learn and teach at NTU
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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particular, the appointee will be expected to: Teach in the Master of Science in Modelling and Simulation program and contribute to undergraduate teaching; Supervise student projects and provide academic
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Learning (Undergraduate Programmes), this position is responsible for academic planning, curriculum coordination, and operational efficiency within NTUpreneur’s undergraduate offerings. The role ensures
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Young and research intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU Singapore has launched the “Care, Serve, and Learn” (CSL
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We are looking for part-time Finance lecturers to teach within the College of Business, Nanyang Business School. Classes are mainly conducted on weekdays; or on Saturdays for make-up classes
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Science, Electronics Engineering or related fields. Strong knowledge in deep learning, pose estimation, 2D/3D detection and segmentation, SAM, foundation models, and 3D computer vision; strong software skills and
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Science (PESS) Department. Job Description Part-Time Lecturers are engaged for teaching duties such as conducting lectures, tutorials and practicum supervision. Please refer to https://www.ntu.edu.sg/nie
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: Qualification: A bachelor’s degree in computer science, computer engineering, electronics engineering or equivalent. Strong background and experience in machine learning and computer vision. Prior experience in