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University is seeking a postdoctoral scholar to support and lead innovative research at the intersection of rheumatology, pain science, and data science. The successful candidate will work on a portfolio of
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laboratories The candidate will also have immediate access to brain PET data acquired from multiple universities, including Stony Brook. This includes large (>30 participants) datasets examining
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the Rosaceae, Citrus, Vaccinium and Pulse crop databases to meet community demand for resources with usable big data aggregated, analyzed, integrated, and visualized, as well as data management and analysis
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genomic analyses on large case-control cohorts to identify risk and response associations for diseases of interest. Performs integrative analyses of other molecular and omics data, such as gene expression
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Posting Information Posting Details Department Renaissance Computing Inst - 637100 Posting Open Date 07/29/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position
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Sheets. Experience with data cleaning, management, and quantitative analysis using R. Experience in computational text analysis, using machine learning and/or large language models (e.g., ChatGPT
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and cellular biology, assist in sorting platform development, perform molecular and in vivo characterization of sorted cells, analyze large-scale bioinformatics datasets to identify novel cell subsets
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medication use Applying frameworks such as the Andersen Behavioral Model (ABM) and 4Ms of Geriatrics Conducting advanced data analysis and predictive modeling Engaging patients, caregivers, and health system
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position in big data analysis, substance use, neurocognition, and tobacco regulatory science. The position entails research on (1) analysis of big data using advanced statistical methods, (2) assessment
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laboratories The candidate will also have immediate access to brain PET data acquired from multiple universities, including Stony Brook. This includes large (>30 participants) datasets examining