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Qualifications: PhD (or equivalent) in Biostatistics, Epidemiology, or a closely-related quantitative field (by start date) Strong training in causal inference methods Experience working with large-scale
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analysis of multiple disease-specific datasets and contribute to the development of novel methodologies in this space. The ideal applicant will have a strong background in bioinformatics methods and a keen
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methods from econometrics. The project extends the work of Proctor and colleagues (Nature, 2018, https://doi.org/10.1038/s41586-018-0417-3 (link is external) ) to other impact variables. Impact variables
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for recent MD and PhD graduates who are passionate about leveraging computational methods to transform trauma and acute care surgery. Fellows will work at the intersection of clinical medicine, data
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Obradović is seeking a postdoctoral scholar to join her research group in the Graduate School of Education at Stanford University. We encourage applications from individuals from a broad diversity of PhD
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and policy methods to real-world questions in acute and population health. Key Responsibilities Conduct and manage research projects focused on emergency medicine health services, care transitions, and
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the resulting data from the experiments. Required Qualifications: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including
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and radiolabeling of the resulting constructs. The fellow will conduct interdisciplinary research to develop unique translational therapeutics or methods to quantify the imaging data. Our federally
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responsibilities include: (1) Conduct computational methods development and analysis for systems-level understanding of host-immune responses to diseases. (2) Collaborate effectively with a team of multidisciplinary
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Qualifications: Have acquired formal training during their doctoral studies in cellular and molecular biology and genetics Be able to work with transgenic mice, preferably with experience Be highly creative