122 high-performance-quantum-computing-"https:"-"https:"-"https:" Fellowship positions at Nanyang Technological University
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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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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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and circuits. Installation and operation of quantum photonic characterization setups and overseeing the progress of the project. Job Requirements: PhD in relevant area (electrical engineering, materials
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Research Associate / Research Fellow – Quantum Hacking and Practical Quantum Security Evaluation (Fraunhofer@NTU) The Fraunhofer Singapore Research Centre FSR@NTU is an independent research centre
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, including organizing research activities, managing projects, and contributing to grant proposals. Job Requirements: PhD degree in communication, psychology, sociology, Human-Computer Interaction (HCI
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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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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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, SuperGLUE, LiveBench). Familiarity with distributed training frameworks and high-performance computing environments. We regret that only shortlisted candidates will be notified. Hiring Institution: NTU
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly