634 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "IMEC" positions at Nanyang Technological University
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program development with topics like abstract data types, trees, graphs, sorting, searching, greedy algorithms, and basic AI classification techniques. Students will gain both theoretical understanding and
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, please view https://www.ntu.edu.sg/newri . The Nanyang Environment and Water Research Institute (NEWRI) invites applications for the position of Research Fellow. Key Responsibilities: The candidate will be
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are seeking a research assistant. The role
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to a deeper understanding of material behaviors, paving the way for the development of next-generation high-performance materials. For more details, please view https://www.ntu.edu.sg/mse/research and
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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, please view https://www.ntu.edu.sg/empower We are looking for an experienced Research Assistant to work closely with a team of researchers, led by PI – Professor Victoria Leong, and to drive and fulfill
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Nanyang Technological University, Singapore https://www.ntu.edu.sg/index A research-intensive public university, Nanyang Technological University, Singapore (NTU Singapore) has 33,000 undergraduate
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian This joint research project is between Nanyang Technological University
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Wee School of Communication and Information’s MSc in Knowledge Management (MSc KM) programme, introduces students to the principles and practices of knowledge discovery and data mining. It covers