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, engineers, and researchers in an effort to develop medical automation research solutions. You will support various engineering and computer science aspects of research projects focused on optimizing combat
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sparse algorithms. The successful candidate will contribute to advancing secure, trustworthy, and efficient AI solutions for scientific applications. Key responsibilities include developing state
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. university groups within CMS. Our instrumentation expertise spans detector operations and upgrades (Level‑1 muon trigger, CSC muon system), tracking algorithm R&D, and future HL‑LHC trigger algorithm
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develop signal processing algorithms to characterize structural health in microreactors and other advanced nuclear reactor technologies. Metrics for success will include scientific output, disseminating
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on using unstructured and overset meshes with high-fidelity algorithms to obtain scale-resolved data. Candidate will also post-process data using data-driven and physics-driven methods to extract fundamental
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development of detectors sensitive to ultra-high dose rates. Developments of computation methods for small-field dosimetry, radiation detection systems used in photon, proton, and electron beam radiation
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 24 days ago
development of data processing tools. The position is for one year with the possibility of reappointment for an additional year. It will involve developing, implementing, and validating novel algorithms
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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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