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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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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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strength of ORNL which is the U.S. Department of Energy’s largest Office of Science laboratory. ORNL is home to two user facilities in manufacturing – the Manufacturing Demonstration Facility (https
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to commit to ORNL’s Research Code of Conduct. Our full code of conduct and a statement by the Lab Director’s office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications
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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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and apply basic GD&T concepts. Experience with ASME piping codes and process piping system design. Experience troubleshooting mechanical or HVAC systems. Understanding of machining and fabrication
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manufacturing, toolpath generation, machine tool operation, and data analysis. As part of this role, you will be tasked to lead the management of project timelines, troubleshoot equipment for routine maintenance
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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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enrichment technology related components using 3D Computer Aided Design (CAD) software (SolidWorks). Create 2D drawings to be used for fabrication and communicate with staff and suppliers through
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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