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within the Julius Kruttschnitt Mineral Research Centre (JKMRC). In this role, you’ll help develop and code mathematical models, analyse data to uncover key insights, and collaborate with industry partners
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of recommendation algorithms based on multiple data related to microorganisms and pathogens, and the implementation of the recommendation system on a testable platform. The work also includes the writing of technical
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and engineering identity. Codes interview transcripts from participants. Prepares reflections for participants. Coordinates activities with undergraduate researchers in multi-site research team
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data Proficiency in advanced statistical analysis methods: structural equation modeling (SEM), robust Poisson regressions Proficiency in handling non-response: weighting and multiple imputation
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
the areas of basic, translational, mechanistic and population research. Position Summary This position will serve as a Clinical Research Assistant within multiple projects, including the Adverse Pathways
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Organization U.S. Department of Agriculture (USDA) Reference Code USDA-ARS-SEA-2025-0099 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete
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models for neurological diseases (e.g., Multiple Sclerosis) and cancers, applying these modeling advances to patient-level outcome prediction, treatment-response modelling, and the discovery of image-based
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Open Date 08/28/2025 Requisition Number PRN42964B Job Title Post Doc Res Assoc w/Ret Working Title Post Doc Res Assoc Job Grade A00 FLSA Code Administrative Patient Sensitive Job Code? No Standard Hours
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documented by peer-reviewed publications. Ability to manage multiple projects and collaborations. Strong team player with excellent communication skills and fluency in English, both spoken and written
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, Department of Radiology, has openings for multiple postdoctoral scholar positions. The research projects will focus on advancing rapid, quantitative, and multiparametric MRI protocols, evaluating