466 computer-science-intern-"https:" "https:" "https:" "https:" "The University of Manchester" Fellowship positions in Singapore
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Sciences, Urban Climate, Architecture Engineering, Building Science, or related fields majoring in Computational Fluids Dynamics (CFD). . Candidate who is in the final stages of PhD studies (i.e. submitted
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understanding of emerging infections through world-class research that integrates immunology, infection biology, pathogen genomics, and computational approaches. This integration drives comprehensive studies
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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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, Computer Science, or related field, with strong background in machine learning. Publications in top-tier journals and/or conference presentations as first author. Proficiency in AI programming languages
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students within the AI4X program Contribute to research proposals, technical reports, and project deliverables Present research progress and findings in internal meetings and academic venues Job Requirements
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effectively both independently and as part of a team Research Associate: • Master’s degree or equivalent experience in Epidemiology, Biostatistics/Statistics, Computational Biology/Bioinformatics, Infectious
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academia, industry, and national laboratories Job Requirements: PhD in Materials Science, Chemistry, Physics, Computer Science, or a closely related discipline. Strong experience with Density Functional
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supervision of Asst Prof Meng Xin from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the strategic adoption of metal additive
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insights from cutting-edge clinical and translational research. More information on the Department’s research portfolio may be obtained from https://medicine.nus.edu.sg/obgyn/. The Core Support Faculty will
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and PhD students on computational mathematics and AI methodologies. Job Requirements: A PhD degree in Applied Mathematics, Computer Science, Engineering, or a related quantitative field. Deep expertise