412 data-"https:" "https:" "https:" "https:" "https:" "https:" "KU LEUVEN" Fellowship positions in Singapore
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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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of Singapore (NUS) invites applications for a Senior Bioinformatician to support and lead advanced research with clinical and translational impact, driving the generation of high-quality data and analyses
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The Division of Banking & Finance at Nanyang Business School seeks a Research Fellow to support data-driven and AI-enabled research in investments and financial markets. The Research Fellow will be
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5, with a particular emphasis on empirical analysis, AI-enabled data construction, and policy-relevant research outputs. Duties and Responsibilities: Design, develop, and execute empirical research
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Job Description Job Alerts Link Apply now Job Title: Research Fellow (CBDS/SES) Posting Start Date: 12/02/2026 Job Description The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a
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-throughput synthesis, automation, and data-driven approaches. Key Responsibilities: Design and execute high-throughput synthesis workflows for solid-state materials, including intermetallics, chalcogenides
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for teaching; however, if the candidate wishes to teach, it may be possible. Qualifications PHD in Computer Science/Quantum Information with a strong record of publications. More Information Location: Kent Ridge
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AI/ML models for predicting materials properties using data-driven approaches, including the treatment of disordered inorganic materials. Develop codes as necessary to assist existing and new code
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implement rigorous study Conduct wet-lab experiments Perform in-depth, critical data analyses Effectively communicate through presentations and high-quality journal publications Assist in supervising research
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and data pipelines to enable real-time data acquisition and closed-loop control. Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous