154 computer-science-intern-"https:"-"https:"-"https:"-"https:" Fellowship positions at Nanyang Technological University
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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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technical reports and documentation to fulfill grant requirements and internal/external stakeholder expectations. Job Requirements: Ph.D. in Materials Science, Chemical Engineering, Physics, or a closely
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NTI-NTU Corporate Laboratory is a collaboration between Nanofilm Technologies International Limited (“Nanofilm”, “NTI”), Nanyang Technological University (“NTU”) and supported by Singapore under
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NTI-NTU Corporate Laboratory is a collaboration between Nanofilm Technologies International Limited (“Nanofilm”, “NTI”), Nanyang Technological University (“NTU”) and supported by Singapore under
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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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research, to design of experiments, to control project spending. Research Fellow will also be dealing with internal, external stakeholders and will be accountable for the successful delivery to cost
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Join Our Team at the School of Biological Sciences, Nanyang Technological University, Singapore The School of Biological Sciences (SBS), part of the College of Science, was established in 2002 with
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: Masters/Ph.D. degree in Electrical/Computer Engineering, specialized in Power Systems/Renewable Energy Planning/Optimization At least 5 years of professional experience with a strong focus on power system
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Electrical and Electronic Engineering, Applied Mathematics, or fields related to Computational Science and Engineering More than 5 years of research experience in the related area Experience in code
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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