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international programs in more than 150 countries. The Pratt School of Engineering at Duke University is one of the fastest rising, highly ranked engineering schools in the nation. The school consists of four
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. The candidate will be expected to work in a team setting with other research staff and PhD students supporting the Project HOPE 1000 pregnancy cohort. The candidate will be expected to conduct independent
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. The successful applicant will possess a PhD or equivalent doctoral degree in the social sciences, including political science, public policy, political ecology, law, geography or another relevant field with some
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) Preferred Qualifications:. A PhD or MD/PhD (or equivalent) in biological sciences Strong research background in cell biology, molecular biology, mouse models
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degree (PhD or equivalent) in Statistics or Biostatistics. Solid training in statistical methods. Experience analyzing clinical trial data. Excellent written and verbal communication skills. Strong
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. You will be co-mentored by Dr. Jason Somarelli, a PhD basic scientist, Dr. Andrew Armstrong, an MD medical oncologist. Minimum Requirements: PhD degree with a background in cancer immunology, prostate
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across the Duke research community. EDUCATION/TRAINING: PhD in electrical engineering, physics, quantum theory/science, expertise in detection and estimation theory. PREFERRED: Statistical signal
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responses. The PhD postdoctoral candidate would be a highly motivated immunology trained individual, interested in B cell signaling, B cell activation and B-T cell interaction, and adept at flow cytometry and
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an exhaustive list of all responsibilities and duties required of personnel so classified. Required Qualifications at this Level Education/Training PhD in health services research, public health, epidemiology