505 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" positions at National University of Singapore
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Lifelong Education (SCALE), established in 2016 as the National University of Singapore’s (NUS) hub for lifelong learning, is both an academic school and a university-wide platform. As a school, SCALE
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proposals are committee-ready, evidence-based, and aligned with agreed learning outcomes, assessment principles, stackability/pathway rules (where applicable), and institutional requirements. Coordinate
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effective administrative support to enable the SHAPES team to carry out its research programmes, learning activities such as workshops, and engagements with scientists, health professionals, members
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Computer Science, AI/ML, Computational Biology, Food Science with computational expertise, or a related field. Experience with natural language processing, machine learning frameworks (e.g., PyTorch
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nowcasting platform that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes
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conferencing and collaborative tools, and video and photo editing skills, is a plus. - Skills in database management, or ability to learn these skills quickly and effectively. - Excellent team player, motivated
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, clinical reasoning, and Team-Based Learning (TBL) facilitation in Phase I. The faculty member will also contribute to curriculum development through participation in curriculum mapping, review processes, and
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⦁ Deliver day-to-day technology and audio-visual support for a high-quality teaching and learning experience. ⦁ Deploy and support hybrid teaching technology (eg. Zoom) supporting either fully virtual
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AWS Management Console, AWS data storage (S3) and virtual machine (EC2) to enable research collaborators through Research Gateway. Enable AWS cloud infrastructure for different researchers within and
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tools (e.g. Power BI, Tableau or Qlik Sense) Experience in applying machine learning techniques and designing algorithms that are scalable and production-grade. Knowledge of database, ETL and data API