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funding matters. Manage academic-related events for graduate students, as well as programme outreach, publicity, orientation and adhoc student events. Consolidation and preparation of data and statistics
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an emphasis on technology, data science and the humanities. We are seeking a motivated Research Associate to support a haematology image-analysis project, contributing to the development of machine-learning and
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environment. 8. Open to Fixed Term Contract. More Information Location: Kent Ridge Campus Organization: College of Design and Engineering Department : Electrical and Computer Engineering Employee Referral
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NTU’s Research Information SystEm (RISE). Manage project database and repository to ensure regular, timely updates and tracking of all key project-related information (e.g., project approval, closure
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members and assessments. • Liaising with faculty members and communicate unambiguously to provide and/or exchange information accurately in all situations. • Provide administrative support to both
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immunophenotyping of colonic tissues. Develop and optimize small animal models of colitis to investigate the mechanistic role of SCFA-producing microbes in mucosal repair. Perform data analysis using computational
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on musculoskeletal health in occupational and community settings. Design and implement cohort-wide studies using questionnaires, interviews, and real-time task observations. Collect multimodal data via motion-capture
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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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agreements in compliance with funder requirements and University policies. Provide information to faculty and research staff on funding opportunities and grant calls. Review grant applications for completeness
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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