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Bloomington Position Summary The Department of Biology is a large, unified department with strong undergraduate degrees, nationally-ranked graduate programs, and world-class research spanning the breadth
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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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optical observing. Among these are the Large Binocular Telescope and 6.5m aperture telescopes located in both the northern and southern hemispheres, and applicants would be eligible to submit their own
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Council, the project will integrate new data collections with existing datasets from recent studies and monitoring programs to understand how pond age, design and management influence trajectories of pond
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Postdoctoral Research Associate for a one-year position to support interdisciplinary research at the interface of data analytics, modeling, and agricultural/environmental systems. The position focuses
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But Degree (ABD) status will also be considered for interviewing. Strong applied quantitative data analytic skills and experience conducting statistical analyses with large databases. Strong writing and
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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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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours 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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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