134 master-"https:" "https:" "https:" "https:" "UCL" Fellowship positions at Nanyang Technological University
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data
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scientific leaders and researchers. For more details, please view https://www.ntu.edu.sg/spms Join the research group of Pinaki Sengupta at SPMS. We are seeking a Research Fellow to contribute to a project
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . The School of Mechanical and Aerospace Engineering (MAE) is seeking to hire a Research Fellow to support the
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group’s research advances polymer network design to achieve high mechanical performance for the evolving demands of modern technologies. For more details, please view https://www.ntu.edu.sg/mse/research
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are seeking a Research Fellow to lead the development and
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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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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research fellow to work on the development of Physics-informed neural networks (PINNs