246 computational-physics-"https:"-"https:"-"https:"-"https:"-"Chalmers" Fellowship positions in Singapore
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Job Description Job Alerts Link Apply now Research Fellow, Computational Biologist (Life Sciences Institute, Neurobiology) University-Level Unit: Life Sciences Institute Faculty/Department-Level
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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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Job Description Job Alerts Link Apply now Job Title: Research Associate/Fellow (Programme Manager) Posting Start Date: 17/07/2025 Job Description: Job Description An exciting opportunity has arisen
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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Health Informatics for PRECISE-SG100K) Posting Start Date: 26/11/2025 Job Description: Job Description Research Fellow (Health
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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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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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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