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Field
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microscopy, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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further year. The P2S2 project aims at developing parton-shower algorithms with unprecedented (logarithmic) accuracy for jet substructure at the LHC. The project also has connections with analytic
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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials, energy
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existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will contribute to building a flexible
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a diverse team of biological and chemical scientists Experience with high performance computing environment (HPC) / cluster job submission Knowledge of statistical methods, data science algorithms
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expertise in existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will contribute to building a
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Schedule: Monday – Friday, 8 a.m. – 5 p.m. Summary The Sedlazeck Lab is seeking a highly motivated Staff Scientist with strong computational and algorithmic expertise to lead and support cutting-edge
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including