1,432 data-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" positions in Singapore
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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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Yih-Cherng Liou (NUS), along with Dr. Caroline Wee (IMCB, A*STAR) are looking for a bioinformatician or data scientist to contribute towards a multi-omics integration effort of transcriptomics
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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 Associate position in the area of efficient
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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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management for at least 2 years after graduation, preferably in the field of education or psychology, research and analysis Experience in data collection Skills to carry out literature reviews Strong skills
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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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sample integrity and compliance with regulatory requirements. - Assist in the development and optimization of biobanking workflows. 5. Data Management and Analysis: - Compile and organize experimental data
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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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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