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generators, protocol analyzer, and power analyzers. Experience with MicroTCA or AdvancedTCA platforms. Background in artificial intelligence (AI) and machine learning (ML) applications. Familiarity with
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optical systems, thermal imaging, pyrometry, spectroscopy, high speed imaging or acoustic sensing. Familiarity with data analytics, machine learning, or signal processing. Knowledge of metal additive
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of AI for science, including scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You’ll help design
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topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and iterative solvers. Successful applications will work
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of AI for science such as: scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You’ll help design, train
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Conduct of Research including being personally responsible for ensuring safe operations by raising safety concerns, using a questioning attitude, considering hazards for every task, and never stop learning
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injection techniques, space charge simulation and theory, and control and mitigation of beam halo and other beam loss mechanisms, and machine learning efforts. Provide leadership to the group to support safe
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feedback, and exchange lessons learned. Conduct quality assessments of work, including document reviews, to verify adherence to specifications and compliance with requirements. Serve as software quality
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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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Expertise in machine learning and big data analysis Excellent written and oral communication skills Motivated self-starter with the ability to work independently and to participate creatively in collaborative