503 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at National University of Singapore in Singapore
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. • Comfortable leading and engaging groups in both indoor and outdoor learning environments, including field-based programmes. • Ability to interact confidently with students of all levels and members
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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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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
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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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to perform the following responsibilities: • Advance NUS Libraries’ Special Collections by improving discovery, access and use of rare and archival materials to support teaching, learning and research