265 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" research jobs at National University of Singapore
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Marine Science Institute (TMSI), we acquire high-quality marine environmental data that supports environmental monitoring. The reliability of our work depends on the quality of our instrumentation and the
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applications for the position of Research Assistant in the Department of Information Systems and Analytics (DISA), School of Computing (SoC). SoC is strongly committed to research excellence in all its
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candidates will be part of a multi- disciplinary group comprising exercise and thermal physiologists, data scientists, biomedical engineers and researchers. This specific role will provide you with a unique
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with the PI and local research teams • Manage field-based data collection, including surveys, interviews, focus groups observational assessments • Design and validate survey instruments and context
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• Experience deploying, testing, and iteratively improving prototypes through user studies • Ability to analyze user study data and translate findings into system improvements • Strong problem-solving
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Job Description Job Alerts Link Apply now Job Title: Temporary Research Assistant (NUSDen) Posting Start Date: 02/03/2026 Job Description • Supporting PI in data entry when classifying pathology
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, hepatologists, and data scientists. The candidate should demonstrate technical experimental excellence as well as the capacity to lead the research team regarding research projects aimed at producing clinically
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(Senior) or Research Associate to join our team at CARE. This role offers an excellent opportunity to gain hands-on experience in project management, quantitative research, data analysis, and scientific
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the APIs or communication layers for the standalone program. Troubleshooting: Assisting with data exchange between the optimization engine and the Warehouse Control System (WCS). Compatibility: Ensuring
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immunophenotyping of colonic tissues. Develop and optimize small animal models of colitis to investigate the mechanistic role of SCFA-producing microbes in mucosal repair. Perform data analysis using computational