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driven individual with a PhD in data science, computer science, biomedical informatics, or a similar background with some experience working with large datasets. Prior experience with healthcare is not
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the Digital Atlas, this project will be highly resolved in space and take novel approaches to modeling uncertainty. It will use and potentially expand a large collection of data compiled by Fabian Drixler and
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Postdoctoral Associate in the Department of Biomedical Informatics & Data Science (BIDS), Yale School of Medicine Job Description We seek full-time Postdoctoral Associates in the areas of highly
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. * Proficiency in R, Python, or related software and programming languages. * Experience with big data, linux systems, and remote computing clusters. * Knowledge of genome-wide approaches and other statistical
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/CT and PET/MR imaging for cardiac applications. Responsibilities involve working with preclinical large animal models, preclinical and clinical PET imaging, image analysis, kinetic modeling, data
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, including coursework and/or research experience in evidence synthesis. 3. Programming experience using large datasets (e.g., R, Python). 4. Outstanding English written and verbal communication skills, with
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organization and maintenance of a large clinical database Support analysis for scientific presentations and quality improvement projects Present outcome data to other clinicians, collaborating sites, and at
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patients. Other areas of research focus that are consistent with the general themes of the labs are also possible. The Kleinstein Lab pairs big data analyses with immunology domain expertise to better
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present data. The ideal candidate will have strong programming experience (R, Python, bash); working knowledge in Linux/Unix environments; experience in the analysis of large datasets; and a solid
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data as well as applications to the HCP-A, A4, ADNI, and other publically available datasets focused on aging and neurodegeneration. The postdoc will receive training in state-of-the-art neuroimaging