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Field
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interventions for preventing overdose, data modeling, national surveys, policy research, epidemiological research, and health services research on pain, addiction, and overdose. Expectations Selection will be
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degree, ideally a PhD, in health economics, medical statistics, data science, epidemiology or a related field. A clear conceptual understanding of causal inference methods such as instrumental variable
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biomarkers and therapeutic targets aimed at improving cardiovascular outcomes for cancer patients. Dr. Li is a physician scientist in radiation oncology whose research integrates genetic epidemiology
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degree, ideally a PhD, in health economics, medical statistics, data science, epidemiology or a related field. A clear conceptual understanding of causal inference methods such as instrumental variable
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doctoral or equivalent degree in Microbiology, Immunology, Biology, Molecular Biology, Biochemistry, Veterinary Pathology, Epidemiology or closely related field at time of hire. Preferred Job Qualifications
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with interdisciplinary methods such as epidemiological and agricultural models. They will join a vibrant and growing research environment that builds on the University of Oxford’s expertise in climate
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in Health Research Methods, Epidemiology, Computer Science, or a related field. Expertise in evidence synthesis and clinical guideline methodology such as network meta-analysis, GRADE. Experience with
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 12 hours ago
Position Details Position Information Position Title Postdoctoral Fellow Posting Number PTAP2767P Department/Unit Community Health & Epidemiology Location Halifax, Nova Scotia, Canada Job Summary
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experience: Essential criteria PhD awarded in genetic epidemiology, statistical genetics, bioinformatics or related discipline Postdoctoral research experience in genetic epidemiology, statistical genetics
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that pose a threat to US agriculture and public health. Potential areas of research include genomic epidemiology, virus evolution, ecological surveillance, ecological modeling and modeling of viral