331 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"DESY" Fellowship positions in Singapore
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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16 Jan 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1
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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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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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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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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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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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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
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low