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under the supervision of Asst Prof Meng Xin from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at developing generative AI tools
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to behavioural and population health data relevant to Singapore’s diverse communities. Develop predictive and explainable machine learning/deep learning/genAI models using multimodal cross-section and longitudinal
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field studies Develop and validate instruments for psychological and behavioural assessment in urban settings Conduct data analysis using relevant statistical, spatial, or computational tools with
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. This position focuses on the development and application of large language models (LLMs) for advancing food informatics, food bioactives research, and sustainable food innovation. The selected fellow
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research strategic development and securing funding Support research data management and documentation Job Requirements: PhD degree in Mechanical/Electrical Engineering or related field At least 1 years of
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progress. Ability and willingness to work some flexible hours. Extensive experience in large-scale pre-training of large language model. Experienced in developing machine learning algorithms and large
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functional networks in healthy developing and aging brain and symptoms-related changes in diseases such as neurodegenerative disorders and psychosis. Computational and machine learning methods are developed
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to the development of synthetic organic or polymer materials and their applications in sustainability. The candidate is expected to have a strong background in Synthesis, Engineering, or Materials Science. More
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to collaborate in developing competitive research grant applications. Applicants must indicate the Research Cluster(s) concerned in their research proposal. Job Description Researchers will work under the
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technically competent post-doctoral research fellow to join an interdisciplinary research project on occupant-centric building controls. This project aims to develop and implement cost-effective occupant