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(SingFarm)—a CREATE-NRF programme focused on building a sustainable, data-driven food production model with strong industry relevance. The programme contributes to Singapore’s ambition of achieving 20 per
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Employee Category: Research Staff Location_ONB: Outram Campus Posting Start Date: 12/02/2026 Job Description The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS
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skills, as well as the ability to work independently. As the assessment tools have already been established and implemented, the project is now at an exciting stage focused on high-quality data collection
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the day-to-day coordination of the project, conducting data collection with children, and contributing to the development of machine learning and deep learning models for early prediction. The research
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the day-to-day coordination of the project, conducting data collection with children, and contributing to the development of machine learning and deep learning models for early prediction. The research
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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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data. A team player with a positive working attitude and is willing to learn and adapt. Proficient in Microsoft Office applications, especially Excel pivot tables and formulas. Experience in SAP would be
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems. We invite applications for a Research Assistant position in the area of efficient
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efficiency and data integrity. Key Responsibilities: Gift Processing: Accurately enter and classify donations in the database, ensuring compliance with donor intent. Acknowledgment: Generate and send timely