135 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:" Fellowship positions at Nanyang Technological University
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photonics, quantum optics, or quantum information science. At least 2 years of relevant research experience with hands-on experimental work in integrated photonics, optical or quantum photonic systems
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Responsibilities: Investigating degradation mechanisms, improving material stability and performance, and collaborating with interdisciplinary research teams. Contribute to high-impact publications, mentor junior
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stakeholder engagement. Responsibilities: Lead research on Rydberg-atom quantum sensing platforms, including experimental design, system integration, and performance characterisation. Develop measurement
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fundamental understanding and practical applications of quantum correlations and information processing. We invite applications for a research position in quantum information science. The successful candidate
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descriptions to support ongoing projects. Job Requirements: PhD or MSc/MEng in Physics, Computer Science, or related disciplines with a focus on quantum physics or quantum information, or digital twins and
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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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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 candidate will collaborate closely with academic researchers and industry engineers to transform research prototypes into deployable, high-performance solutions aligned with industrial requirements. Key
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. To perform any other duties related to the research program. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly
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language models, with multiple publications in leading conferences and journals. Familiarity with distributed training frameworks and high-performance computing environments We regret that only shortlisted