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, qualification/certification, additive manufacturing feedstocks, carbon fiber and composites, caron-carbon materials, machining, data analytics, metrology, flexible automation and systems research. Successful
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Qualifications: BS in a science, engineering, business administration or industrial-organization psychology with a minimum of two years experience. Possess an advanced level of knowledge in office computer systems
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generating fusion energy. This research will focus on the chemical speciation and transport of tritium in the molten salt blankets using ab initio quantum simulations, machine learning potentials, and
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, qualification/certification, additive manufacturing feedstocks, carbon fiber and composites, caron-carbon materials, machining, data analytics, metrology, flexible automation and systems research. Successful
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monitoring in manufacturing environment Develop modular, extensible workflows for data processing Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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awareness and understanding of open relevant research conducted throughout the DOE complex and the world. Basic Requirements: PhD in Mechanical Engineering, Electrical or Computer Engineering, or related
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-impact problems and to shape the future of intelligent manufacturing. Major Duties/Responsibilities: Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral