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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
to 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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Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review
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. Participates in the UMN PDA: post-doc program activities: presentation and preparation of data into figures, written project updates, oral presentations (including lab meetings, post doc seminars, and
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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team of undergraduate/postgraduate researchers. Candidates should be able to multitask parallel evolution experiments with phenotypic and genomic analyses. Job Duties and Responsibilities: Typical tasks
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approaches in a coherent framework. Rather than treating these disciplines in parallel, Brown PPE emphasizes methodological integration — reconnecting traditions that once addressed questions of justice
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ensures that talented students from all economic backgrounds can afford a Princeton education. Connections working at Princeton University More Jobs from This Employer https://main.hercjobs.org/jobs
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the collective behavior of complex systems, understanding how micro- level interactions drive macro-level evolution. Practical experience with high-performance computing (HPC) and parallel processing to enable
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data