125 computational-physics-"https:"-"https:"-"https:"-"https:" Fellowship positions at Nanyang Technological University
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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transfer activities and engagement with industry or governmental stakeholders. Requirements: PhD in Physics, Engineering, or related field. Extensive experience in Rydberg atom experiments and
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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
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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Corporate Laboratory is seeking to hire a Research Fellow. The selected candidate will innovate hybridized composite materials and thin film coatings. Key Responsibilities: Work on plasma physics process and
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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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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Postdoctoral Fellow to contribute to building computational
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-dimensional material systems, contributing to NTU’s leadership in physics, materials science and engineering research. Key Responsibilities: Conduct independent and collaborative theoretical and computational
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SPMS is a School under NTU College of Science. Our School is organized into two divisions: the Division of Mathematical Sciences and the Division of Physics and Applied Physics. We are home to
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in numerical analysis, partial differential equations (PDEs), and scientific computing. Solid background in machine learning theories, with specific experience in Physics-Informed Machine Learning