830 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" "UNIV" "UNIV" positions at Nanyang Technological University
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The Office of Information, Knowledge and Library Services (OIKLS) at Nanyang Technological University seeks a passionate individual to transform library spaces to meet evolving needs of users and to
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reporting to funder. Assist with compilation of data on 5th tranche funding for financial reporting purposes. Liaise with different stakeholders and build strong relationships with NIE Finance and MOE. Lead
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for machine learning Competent in soft skills / general personality traits e.g. information visualization, interaction design We regret to inform you that only shortlisted candidates will be notified. Hiring
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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policies and support year-end audit/tax filing processes Ensure SOPs are properly documented Manage research project financial data and system to ensure timely and accurate grant submission in accordance
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who enjoy working in a fast-paced academic environment and engaging multiple stakeholders. Key Responsibilities: Analyze and consolidate various data to support Undergraduate Programmes decision-making
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of academic activities and events. Ensure accurate record-keeping and smooth delivery of teaching and programme operations. Participate in TCM clinical research by supporting patient recruitment, data
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guide Utilise low-code platforms such as UiPath, and Outsystems to develop automated applications Ensure data integrity, security and proper error handling Perform testing and quality assurance activities
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research grants in the above areas Job Requirements: A PhD degree in Computer Science, Data Science, Engineering, or a related field. Research experience in Computer Vision, Image Processing, Multimedia
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designs are production-ready. Support development of test rigs, SOPs, and quality benchmarks for scaled stack validation. Analyze test data and drive design improvements based on real operating feedback