307 machine-learning "https:" "https:" "https:" "UCL" Fellowship positions in Singapore
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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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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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peer-reviewed journals and/or top-tier conferences. Knowledge & Skills: Strong foundation in machine learning, deep learning, and algorithm development. Proficiency in scientific programming (e.g
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and the associated vulnerability patterns in aging and neuropsychiatric disorders using multimodal neuroimaging and machine learning methods. We are interested in the large-scale brain structural and
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, economics, or a closely related field. Excellent knowledge of computational linguistic tools and machine learning techniques. Experience with data analysis with Python and STATA. Prior experience in
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characterization of integrated memristor devices and systems. • Develop algorithms and system-level integration strategies to harness the capabilities of AI accelerator for machine learning and deep learning
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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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. Experience with data-driven modelling, machine learning, or AI applications in energy systems is an advantage. Familiarity with modelling of energy networks, district cooling systems, or integrated urban
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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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for machine learning and artificial intelligence, with a strong emphasis on developing and applying models such as LSTM and other time-series analyses to predict the longevity and behaviour of bioactive