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NSF funded projects, advancing the knowledge about distributed systems, developing novel algorithms for distributed resource and workload management, simulating and emulating systems, as
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE’s SWARM project (https://swarm-workflows.org
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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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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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 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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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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on developing advanced new algorithms, testing and validation, and applications in medical neuroimaging and non-imaging modalities. The candidate will contribute to the overall research goals and objectives
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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