77 distributed-computing "Institute for Basic Science" Postdoctoral positions at Oak Ridge National Laboratory
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intersection of applied mathematics, computational science, and high-performance computing. The successful candidate will help develop advanced scientific computing methods and deploy them on state-of-the-art
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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laboratories, and scientific computing. This position is motivated by emerging national priorities in AI for science, including the DOE Genesis Mission: transforming science and energy through AI-enabled
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complex challenges in science, energy, national security, and health. Our researchers develop scalable machine-learning models, deep-learning architectures, and data-driven methods for platforms ranging
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Requisition Id 16197 Overview: We are accepting applications for a Postdoctoral Research Associate position who will focus on the intersection of material science, materials characterization
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Requisition Id 16779 Overview: We are accepting applications for Postdoctoral Research Associate positions in Data Science for Advanced Manufacturing that will focus on the development of next
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workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data
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follow ORNL cybersecurity policies and guidelines. Basic Qualifications: Ph.D. in Quantum computing, Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely
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Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing and Computational Sciences Directorate (CCSD), at Oak Ridge National Laboratory (ORNL). Major
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workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The