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interested applicants for a faculty position in the Pediatric Cancer Outcomes Program. We are seeking strong epidemiology candidates in the areas of pediatric cancer outcomes research and public health-related
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demonstrated capacity to publish, and the potential to secure external funding, and either have prior experience or be interested in the epidemiology, clinical research, and public health aspects of vision
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-time faculty and enrolls over 2000 full and part-time graduate students in its masters and doctoral programs including Global MPH programs in the Departments of Environmental Health and in Epidemiology
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of children served by our Center. Scientists with backgrounds in the fields of epidemiology, implementation science, public health, health services utilization, and clinical trials are appropriate
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locations, Hostile Environment Awareness Training (HEAT) will be required. The position brings and develops expertise in the fields of health science, epidemiology, data science, and programming languages as
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conferences. Performs related responsibilities as required. MINIMUM QUALIFICATIONS: A master's degree in public health (epidemiology) or related research intensive field from an accredited school. At least one
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. Experience with Oracle, Microsoft SQL Server and MySQL strongly preferred PREFERRED QUALIFICATIONS: A Ph.D. in Biology, Biostatistics, Ecology and Evolution, Epidemiology, Mathematics, or Global Health with a
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: PhD in nutrition, epidemiology, or related fields with a strong background in data management and analysis. Experience with managing complex data sets. Extensive experience working in global health in
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-training is required. International travel required. PREFERRED QUALIFICATIONS: A Doctorate degree in a public health field (epidemiology, demography, biostatistics, parasitology, etc.) with at least seven
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research project datasets. Familiarity with epidemiology and biostatistics methods, especially experience with regression techniques for survival, longitudinal and count outcomes. Familiarity with predictive