147 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" Fellowship positions at National University of Singapore
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Economics or related discipline. Teaching and research experience in Health Economics / Econometrics are highly desirable. Experience in quantitative data and statistical analyses (preferably with health
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intelligence, neuroimaging, data science, and public health to advance early detection and prevention of cognitive decline and ageing-related brain disorders. The research team works closely with local and
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will include designing and developing smart databases of various unstructured and non-traditional information related to corporate environmental and social impacts. There are no teaching obligations
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participants, and ensure compliance with research ethics and data privacy requirements. This role includes some project management, including coordinating tasks, tracking and reporting process, and collaborating
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gaze tracking (including years of master's and/or Ph.D.) Good knowledge of the anatomy and physiology of the visual system Knowledge in data processing, analysis and statistics Excellent data
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gaze tracking (including years of master's and/or Ph.D.) Good knowledge of the anatomy and physiology of the visual system Knowledge in data processing, analysis and statistics Excellent data
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intelligence. The responsibilities of the role will include designing and developing various analytical frameworks to analyze structure, unstructured and non-traditional data related to corporate financial
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techniques such as CRISPR/Cas9 gene editing, flow cytometry, RNA sequencing, and imaging technologies. Analyze and interpret experimental data using bioinformatics/statistical tools where appropriate
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, conferences and ARI social events. Other benefits that the University provides and information about working at NUS and living in Singapore are available at Why Join Us . Terms and conditions, according
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Computing (HPC) applications. Qualifications/Requirements Qualifications / Discipline: - PhD’s degree in Physics, Materials Science, Computer Science, Data Science, Artificial Intelligence, or a related