664 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nanyang Technological University
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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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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 work on the thermal catalysis for CO2
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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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translate this understanding into disease alleviation and prevention. For more details, please view https://www.ntu.edu.sg/medicine/research/research-programmes/nutrition-metabolism-health We are looking
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(ELL) Department. Job Description Part-Time Lecturers are engaged for teaching duties such as conducting lectures, tutorials and practicum supervision. Please refer to https://www.ntu.edu.sg/nie
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A Postdoctoral Fellow position is available in Prof. Tong Ling’s Lab (https://www.tonglinglab.com ) at Nanyang Technological University, Singapore. The successful candidate will work with our
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in Singapore alongside DSO National Laboratories, Defence Science and Technology Agency (DSTA), Temasek Laboratories @ NUS and @SUTD and the local defence industry. For more details, please view https
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Publish research papers in top-tier journals and conferences Job Requirements: PhD degree in Electrical and Computer Engineering or Computer Science Strong publication record with papers accepted/published
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Development (PCHD) Department. Job Description Part-Time Lecturers are engaged for teaching duties such as conducting lectures, tutorials and practicum supervision. Please refer to https://www.ntu.edu.sg/nie
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations