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of global aerosol emissions using large ensemble data from RAMIP and other data sources. Lead writing of peer-reviewed publications and present findings at scientific conferences. Contribute scientific
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
, or translational breast cancer research. The successful candidate will lead research efforts using rich molecular and epidemiologic data from the Carolina Breast Cancer Study (CBCS), a large, diverse population
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and studying the phenological migration behavior of small insects using the terra-mobile platform on the Salter Research Farm. Analyze data and summarize results by writing scientific papers
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large-scale whole genome and whole exome sequencing, RNA-seq, ATAC-seq, proteomics, and metabolomics data in a well-established cohort of childhood cancer survivors with clinically ascertained deep
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%-100% effort. Qualifications All required qualifications must be documented on application materials. Required Qualifications PhD in Biomedical Eng., Computer Science/Eng., Electrical Eng., Math
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
Posting Information Posting Details Department Epidemiology - 463501 Posting Open Date 08/29/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position Title
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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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pregnancy cohort, a large, longitudinal study based in Durham, North Carolina, to investigate how prenatal and early-life environmental exposures influence immune-related outcomes during pregnancy and early
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occasional travel and a requirement to spend a few months a year at our secondary location, Riverside, California. We are seeking a postdoctoral candidate with experience in EEG data acquisition and analysis
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for projects examining questions in cardiovascular disease using extremely large data sets comprised of routinely-collected clinical data · Developing and maintaining requirements for access to Truveta Data and