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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
Posting Information Posting Details Department Marsico Lung Inst - CF Center - 426401 Posting Open Date 07/27/2026 Application Deadline 08/02/2026 Open Until Filled No Position Type Postdoctoral
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healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics
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. The PDRA will develop a large-scale process for photoreforming chemistry, which uses solar energy to upcycle plastic waste into fuels and valuable chemicals. The PDRA will oversee the assembly
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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subtomogram averaging Integrate the structural data with the lab's interaction mapping, proteomics and computational modeling Design and run follow-up cell biology experiments to test mechanistic hypotheses
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publications prior to the panel interview. In addition to further excelling your skills in Computer Vision/Big Data/Machine Learning analyses, this opportunity enables you to: - Work closely with clinicians
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for data management and analysis (e.g., STATA, SPSS, SAS, R), and familiarity with AI tools for data processing, nutrient coding, and analysis of large food and dietary datasets, and the ability to work well
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) Contact information for three references Choose Duke. Join our award-winning team as identified by Forbes magazine as America’s Best Large Employer 2024 and be part of an inclusive culture that values
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(programming and advanced data analysis, experience with the analysis of large and complex datasets, GIS, data management) Process-oriented thinking and hydrological process understanding Some experience in