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. An independent organisation, its founding partners are the Medical Research Council, Cancer Research UK, Wellcome, UCL, Imperial College London and King’s College London. The Crick was formed in 2015, and in 2016
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programme is a prerequisite. See admission requirements: PhD in Social Science Applicants must meet the grade requirements for PhD admission (typically a B average in the master’s degree). Strong English
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. Admission to the faculty’s PhD programme is a prerequisite. See admission requirements: PhD in Social Science Applicants must meet the grade requirements for PhD admission (typically a B average in the
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project that will enhance Population Health research in Oxford. Applicants should have an MSc in a subject relevant to Population Health (e.g. medical statistics, epidemiology, health economics, sociology
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assistant if required. Applicants should have a relevant PhD, significant postdoctoral experience, a clear, feasible and relevant research plan and be an author of high impact papers. You will be required
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provided to support research programme costs. Applicants should have, or have submitted a relevant PhD by the start date, have a clear, feasible and relevant research proposal and the ability to manage their
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in the research project - “The Hong Kong Polytechnic University - Convergent International Travel Co., Ltd. International Tourism Digital Intelligence Joint Innovation Lab”. Qualifications Applicants
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 8 days ago
*Applications will be reviewed on a rolling-basis. FDA Office and Location: Multiple research opportunities are available immediately within the Office of Non-Prescription Drugs (ONPD) / Office of
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 8 days ago
*Applications will be reviewed on a rolling-basis. FDA Office and Location: A research opportunity is available within the Division of Applied Regulatory Science (DARS), Office of Clinical
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable