292 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" Fellowship positions in Singapore
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modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in or experience in environmental exposure
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of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop software prototypes for AI-for-Science systems tailored to scientific discovery and data
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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context. • Conduct statistical analyses, longitudinal modelling, or machine learning approaches as appropriate. • Develop documentation, codebooks, or tools to support reproducible research. • Lead
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Research Fellow to undertake responsibilities in
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function. Over the years, SBS has attracted talented individuals from around the world and Singapore to join as scientific leaders and researchers. For more details, please view https://www.ntu.edu.sg/sbs
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the National Cancer Centre of Singapore (NCCS) and Singapore General Hospital (SGH). Excited and motivated individuals are encouraged to apply. For more information, please visit: https://dr.ntu.edu.sg/cris/rp
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, 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 grow. We welcome you to join our community
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. The key objective is to support efforts to advance fundamental and high-impact research. For more details, please view http://www.ntu.edu.sg/spms . Join the laboratory of Shilei Ding at SPMS. We are seeking
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related