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the Bartesaghi Lab at Duke University to work in the development of image analysis and machine learning methods applied to protein structure determination using single-particle cryo-electron tomography (ET
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. The project goals are to evaluate the geochemical characteristics of acid mine drainage (AMD) fluids and treatment solids at sites that are known to be enriched in rare earth elements, cobalt, and other metals
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Policy Research Assistant Hybrid (Washington, DC or Durham, NC) Margolis Institute for Health Policy
health care delivery and payment reform. This position will support Duke-Margolis projects with a variety of complex activities in research, writing, and analysis of quantitative and/or qualitative data
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Policy Research Assistant Hybrid (Washington, DC or Durham, NC) Margolis Institute for Health Policy
or NC, respectively) and in-person team collaboration. Work Performed Support and perform a variety of complex activities in research, writing, and analysis of quantitative and/or qualitative data within
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); in vivo surgical techniques; ex vivo glial cell cultures and analysis; endpoint tissue collection and processing (e.g., flow cytometry, immunohistochemistry, ELISAs, Westerns, qPCR); microbiome and RNA
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, engaging with other data analysts, students, post- docs and faculty on the team Conduct comprehensive high-throughput multi-omics data analysis and epidemiological analyses; Apply biostatistics and cancer
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directions that can seed future independent positions. Work Performed Depending on candidate interests and expertise, projects may involve: Analysis of global dietary patterns using genomic approaches
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physiology, behavioral analysis, genetic models, chemistry and toxicology to examine the effects of flavor additives in electronic cigarettes and other tobacco products on nicotine use initiation and health
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, including literature review, experimental design, data analysis, collaboration, and dissemination of findings through conferences and publications. Apply for fellowships and awards, and provide mentorship
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system. For the meta-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine