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high-performance MRAM devices for advanced computing memory applications. Manage project activities by liaising with international semiconductor companies, research institutes, and foundry partners. Lead
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research in photonics, optical imaging, computational sensing and related interdisciplinary technologies. We are looking for a Research Fellow to conduct research in advanced optical imaging, structured
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learning model to realize performance optimization afterward. Key Responsibilities: Design and develop high-throughput synthesis platform for realizing rapid and smooth synthesis of disordered crystalline
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) Application Deadline 1 Aug 2026 - 00:00 (UTC) Country Singapore Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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The Signature Research Programme in Emerging Infectious Diseases (EID) aims to pioneer our understanding of emerging infections through world-class research that integrates immunology, infection
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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 Research Fellow will join a translational cancer research program focused on understanding the molecular mechanisms underlying haematological malignancies, including multiple myeloma (MM), acute
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computation in the face of malicious adversaries. Key Responsibilities: To conduct high quality research in cryptography (Average of at least 2 publications per year in high quality journals and conferences
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Senior Research Fellow (Human Factors / Human-Computer Interaction / Engineering / Computer Science)
contributing to high-impact publications, engaging with industry and regulatory stakeholders, mentoring junior researchers and students, and supporting project delivery and reporting. Responsibilities: Lead
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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