301 cloud-computing-associate-professor-"https:"-"https:" positions at Oak Ridge National Laboratory
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Requisition Id 15315 Overview: We are seeking a Postdoctoral Research Associate who will support the Accelerator Physics Group in the Research Accelerator Division, Research Accelerator Division
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solutions to compelling problems in energy and security. We are seeking a Research Associate (RP02) who will support the Plasma Exhaust and Particle Control (PEPC) Group in the Fusion Energy Division, Fusion
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Requisition Id 15769 Overview: The Computational Hydrology and Atmospheric Science (CHAS) Group at Oak Ridge National Laboratory (ORNL) is seeking a highly motivated Postdoctoral Research Associate
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Isotope Program and other DOE mission areas. This has been a quickly expanding program at ORNL and offers significant opportunities for professional growth. The team demonstrates a collective excitement for
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technicians and field engineers in the build, integration, testing, and commissioning advanced grid sensors and associated instrumentation for medium-voltage and distribution systems, including high-resolution
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centered on Microsoft Azure and related AI cloud technologies with High Performance Computing (HPC) for on premise AI environments and Azure, AWS, and GCP for off premise environments. Major Duties
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Requisition Id 15625 Overview: We are seeking a Postdoctoral Research Associate to advance modeling and AI-driven analysis for magnetic quantum materials, with a focus on neutron scattering and
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we treat one another, work together, and measure success. Operations Handle daily operations, coordinating the delivery of IT support across cloud platform operations. Work with team members to craft
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environmental conditions, and predicting photosynthesis at multiple scales. The selected postdoctoral scientist will work with a team of mathematicians, computational scientists, plant geneticists and
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candidate will bring a strong foundation in systems architecture, a working knowledge of cluster computing and scaling, and a passion for advancing the security of AI systems under real-world and simulated