178 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" positions at Oak Ridge National Laboratory
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, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
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of quality initiatives, assesses satisfaction, and exchanges feedback and lessons learned. Analyze, interpret, and communicate quality and performance data to management in support of established metrics and
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, computer engineering, business, science, or a related field of study and a minimum of eight to twelve years of Windows systems engineering and administration experience is required for consideration
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modeling, machine learning, and automated experimentation. Mentor and support Group Leaders to ensure excellence in research performance, staff development, inclusion, and cross‑disciplinary collaboration
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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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toward integration of hydropower with battery storage and other technologies. Computational and analytical skills : Demonstrated ability in selecting and deploying machine learning tools (Random Forest
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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comparative research across Mojo, Julia, Rust, and vendor toolchains. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or related field. Experience with LLMs or agentic AI frameworks
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to a general science-interested audience as well as a more scientifically trained audience such as researchers and sponsors. Should also have a firm grasp of standard business computer software (e.g