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funding. Requirements A PhD degree in a relevant discipline (e.g., civil engineering, computer science, AI, architecture, or related fields); A strong publication track record; Experience with Building
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Ref.: 532734 Work type: Full-time Department: Department of Urban Planning and Design (01300) Categories: Senior Research Staff & Post-doctoral Fellow The Department of Urban Planning and Design invites applications for two positions as Research Assistant Professor (RAP) in Urban Analytics or...
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, information technology, engineering or a related discipline. They should have at least 4 years of teaching, school-based support, or project management experience. Strong communication skills, and proficiency in both
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the possibility of renewal subject to satisfactory performance. Applicants should possess a Ph.D. degree in Dentistry, Medicine, Engineering, or relevant disciplines. He or she should have a good command of written
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collaborative multi-omic research projects relating to gut microbiota and vascular and brain health Involve in the design, implementation, and testing of statistical and AI software for analysing large healthcare
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on research projects related to health service research and/or global healthy aging promotion, and assist in research grant application, project leadership, data analysis and research dissemination. A highly
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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, Nanomedicine & Advanced Therapeutics at the Department of Pharmacology and Pharmacy (several posts) (Ref.: 532606) We now invite applicants to join the Science, technology, engineering, and mathematics Lab
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Hong Kong University of Science and Technology, Physics Position ID: HKUST -Physics -POSTDOC1_KTLAW1 [#29811] Position Title: Position Location: Hong Kong, Hong Kong [map ] Subject Areas: Condensed
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of family and mental health are preferred. They should be competent in advanced quantitative analysis (e.g. SEM, multi-level modelling, factor analysis) and experienced in using statistical software (e.g