2,007 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "University of London" positions in Singapore
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Employee Category: Research Staff Location_ONB: Outram Campus Posting Start Date: 27/01/2026 Job Description The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS
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SPMS conducts cutting-edge research in quantum science and technology, with strengths in quantum information theory, quantum communication, and quantum resource theories. We aim to advance both
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the mechanisms contributing to sporadic ALS progression, helping to pave the way for novel therapeutic strategies. They will collaborate closely with data scientists and experimental colleagues to ensure thorough
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programmes. Collect and analyse data on education systems in Singapore and internationally to support NUS’s overall admissions strategy. Collaborate with internal and external stakeholders to ensure a smooth
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HOP Tool (HOP V1) and preliminary tool completion guide. In Phase 2, HOP V1 will be piloted with K2 educators and will be refined into HOP V2 based on psychometric data and stakeholder feedback. In
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managing the scheduling, data collection and quality assurance of EEG, MEG, fNIRS and fMRI research projects. You will also collaborate with researchers and directors to ensure sound technical support for
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the Open Science and Research Services function with the Office of Information, Knowledge and Library Services (OIKLS). The successful candidate will provide research services to support NTU researchers in
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NTU’s College of Humanities, Arts and Social Sciences (CoHASS) includes four schools: Humanities; Social Sciences; Art, Design and Media; and the Wee Kim Wee School of Communication and Information
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processes, including application management, interviewing scheduling, and applicant communication. Provide information to prospective students, parents, and schools regarding admissions and financial aid
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data analysis through to deployment and documentation. Applied Machine Learning: Possess deep, practical knowledge of machine learning fundamentals, with proven experience applying algorithms to solve