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                candidate will receive training in analyses of single-cell and bulk-tissue multi-omics data and be expected to participate in multiple projects involving design, implementation and integration of large-scale 
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                The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days agoto contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program 
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                experience in one or more of: large-scale data analysis, time-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department 
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                subject to continuing based on the availability of funding. The work will focus on the production of large polarimetric maps from the SOFIA data. The position is planned for two years, with a possible 
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                public health, health policy, health services research, data science, epidemiology or a related field. Strong data analytic skills, including experience with SAS and/or R. Excellent writing and 
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                University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days agodiversity and brings together expertise in software engineering, big data, clinical informatics, and medicine. Key Responsibilities Collaborate with researchers to design, develop, and refine large language 
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                , and radiation. Research activities would include contributing to experiments using the Europa Tower (Stone Aerospace Facility) to provide cryogenic temperatures, hard vacuum, a large ice column, and 
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                , and contributing to a robust data infrastructure that makes large-scale, multimodal datasets FAIR and AI-ready. You will publish findings in high-impact journals, present at major international 
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                . Department Specific Functions Research and Development: Develop and apply AI and machine learning models to analyze large-scale cancer datasets, including genomics, transcriptomics, and proteomics data. Data 
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                in core methods of machine learning/artificial intelligence. ● Experience with data warehousing and building large, curated datasets with protected health information, suitable for training large