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spectroscopy. Experience designing custom experimental hardware, vacuum systems, and plasma diagnostics. Experience applying machine learning methods for predictive analysis. Expereince with the Python
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. Represent ORNL and the Learning Systems Group by giving talks at public forums (conferences, workshops, guest lectures, etc.). Basic Requirements: Ph.D. in Computer Engineering, Electrical Engineering
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Demonstrated experience in control theory and control system design (e.g., model predictive control, feedback control, adaptive control) Experience applying machine learning/AI to engineering systems Proficiency
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; (ii) advanced free energy simulation methods (e.g., meta dynamics, umbrella sampling); (iii) development and/or application of machine learning potentials (iv) modeling of molecular reaction, (v) Markov
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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
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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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. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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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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analytics, including correlation analysis and machine learning techniques. Preferred Qualifications: Experience with microstructure characterization techniques (SEM, EBSD, TEM, XRD). Experience in mechanical