292 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship research jobs in Singapore
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experience with management and strategy research, economic modelling and statistical analyses are essential. Familiarity with data mining, machine learning and computation techniques, especially in the context
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian You will be part of a dynamic research team working on topics relevant
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computer vision and machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community. To provide guidance and support to
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, Singapore, and the broader public. For more details, please view https://www.ntu.edu.sg/medicine/CMM . The role will involve investigating the influence of modifiable environmental risk factors, dietary and
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insights from cutting-edge clinical and translational research. More information on the Department’s research portfolio may be obtained from https://medicine.nus.edu.sg/obgyn/. The Core Support Faculty will
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international law. More on CIL can be found here: https://cil.nus.edu.sg/ About the Oceans Law and Policy Team: Ocean Law & Policy is one of CIL’s core programme areas and was established over 10 years ago. It
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Science of Learning research team in developing brain-based machine-learning predictive models for early identification of mathematical learning difficulties in kindergarten and early primary level students
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role in designing composites materials using inorganic solid electrolytes using computational modelling and machine learning. Qualifications • Ph.D. in Materials Science, Chemistry, Physics, or a
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in empirical analysis using econometric, machine-learning, and language-modeling techniques. Conducting literature reviews and synthesizing existing academic research to support ongoing projects
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aims to improve electrodialysis (ED) for REE separation by developing advanced membranes and integrating AI-driven optimization techniques. By combining materials innovation with machine learning