2,012 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" "Univ" positions in Singapore
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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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behavioral science will be a plus. The candidate will be expected to: Conduct and write systematic literature reviews and meta-analyses Coordinate and participate in fieldwork and data collection Conduct
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biomedical laboratory work; assist with experimental workflows as required Qualifications Diploma in Biotechnology, Biomedical Science, or a related field Basic computer proficiency (email, Microsoft Office
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optimise finance systems, championing data-driven insights. Lead, motivate, and develop the finance team. Foster a collaborative, service-oriented culture and manage change for new processes and technologies
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., website, newsletters) to showcase successful collaborations and pedagogical innovations. Monitor the progress of engagement initiatives, collect data and conduct analyses to evaluate the impact and
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education, public sector, or innovation environments. Exposure to HRIS systems and process automation. Track record in candidate experience and stakeholder management. More Information Job Type: 2-year
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responsibly. Commitment to full-time, on-campus work at NUS Business School. Preferred Qualifications Prior research experience in accounting or finance projects. Familiar with text or image data processing
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/Requirements Qualifications / Discipline: - PhD’s degree in Physics, Materials Science, Computer Science, Data Science, Artificial Intelligence, or a related discipline from a strong institution. Skills
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experience with management and strategy research, economic modelling and statistical analyses are essential. Familiarity with data mining, machine learning and computation techniques, especially in the context
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. Teaching and research experience in Health Economics / Econometrics are highly desirable. Experience in quantitative data and statistical analyses (preferably with health-economic data) with modelling