858 machine-learning-"https:"-"https:"-"https:"-"https:"-"RAEGE-Az" positions in Singapore
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and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design, aimed at developing
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, machine learning, and deep learning models. Key Responsibilities: Develop and apply time-series forecasting methods for semiconductor equipment health monitoring. Analyze equipment degradation data
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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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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 vulnerable groups
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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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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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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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innovation. The Platforms Engineering Group builds and operates the infrastructure and systems that enable AI practitioners across AISG's programmes to develop, train, and deploy machine learning models
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, Imperial College London, Ashoka University, the Communicable Diseases Agency Singapore (CDA), the National Environment Agency Singapore (NEA), the Machine Learning & Global Health Network (MLGH), and wider
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fields. You will be an integral member of an inter-disciplinary Science of Learning research team in developing brain-based machine-learning predictive models for early identification of mathematical