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on large volume of data Well-organized with good monitoring and follow-up skills within tight deadlines Confidentiality, tact and discretion when dealing with confidential data Positive attitude, able
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outbreaks. Engaging with SSHSPH’s large-scale cohort studies, such as the Singapore Chinese Health Study (SCHS) and the Singapore Multi-Ethnic Cohort (MEC) Study, to contribute to the development and
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for the administrative management of the Open Fund - Large Collaborative Grant (OF-LCG) Programme, along with various business-related functions. This will involve cross-institutional liaison and project management
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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of successful implementations. • Define and operationalise support model for products across the portfolio. Qualifications Experience • Degree in Information Technology, Computer Science, Computer Engineering or
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complex information clearly. Duke-NUS-owned platforms : • Edit content for internal and external publications, and social media platforms. • Build relationships with faculty, staff, alumni, students
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, Control Engineering, Mechatronics, Computer Science, etc. Strong background in AI, Large Language Model, autonomous driving, deep learning, interaction modelling, prediction, robotics and automation
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opportunities aligned with CDE’s goals. • Oversee the analysis of historical CDE funding data to assess research capabilities, identifying both strengths and gaps. • Develop recommendations that inform
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deep research capabilities in sustainable and green finance, provide thought leadership in the sustainability space, and shape sustainability outcomes across the financial sector and the economy at large
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and the economy at large. This role is ideally suited for those wishing to work in academic or industry research in quantitative analysis, particularly in the area of machine learning and artificial