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The Signature Research Programme in Health Services Research & Population Health (“HSRPH”) in Duke-NUS Medical School is a centre of academic excellence for research and education of health systems
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to identify biological, clinical, lifestyle, and social determinants of healthy ageing Design and conduct observational studies and secondary data analyses in collaboration with the clinical trial team Develop
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) working on a wearable sensor development project. This project aims to develop a Wearable Sensor Network that integrates wireless, miniaturized sensors to measure physiological parameters across multiple
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and collaborative projects. Work with investigators to develop culturally sensitive cognitive interventions, and thereafter provide interventions as a service for clinical trials. Provide
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epidemiology, remote sensing, machine learning and/or meta-analyses to identify impacts of environmental change on infectious disease dynamics and design targeted surveillance approaches; - Develop and implement
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and education activities in two divisions: Division of Mathematical Sciences (MAS) and Division of Physics and Applied Physics (PAP). MAS covers diverse topics ranging from pure mathematics
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, efficiency, parameterisation, uncertainty quantification, and/or surrogate modelling. The research may involve the use of observational, experimental, or high-fidelity numerical data to train, validate, and
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of multi-modal datasets, including MRI/fMRI, behavioural and audio data Develop reproducible statistical and machine learning analysis pipelines Support grant writing, ethics submissions and project
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-based analysis of maritime decarbonization pathways, compliance strategies, and regulatory impacts. Develop analytical and modelling frameworks to assess compliance costs, fuel/fleet transition and
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for back-end-of-line (BEOL) integration with CMOS. Key responsibilities include: • Develop and optimize ALD processes for oxide semiconductor channel materials (e.g., IGZO, ITO, IZO) and BEOL-compatible