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Qualifications: Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field. Strong proficiency in Python, with additional experience in C, C
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Electrical Engineering Fundamental understanding of power system modeling, numerical methods and linear control theory
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deployment, monitoring, and optimization of complex scientific data streaming workflows for current and future production infrastructures. The project will involve close collaboration with a team of systems
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. Position Requirements A Ph.D. in Materials Science, Electrical Engineering, Applied physics, or related field. Must have been received within the last 5 years or upcoming year. Normal daytime work hours at
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Ph.D. in electrical engineering, applied physics, physics, or related field. Must have been received within the last 5 years or upcoming year Normal daytime work hours at the Argonne site, but occasional
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candidate will engage in programs involving expertise in thermal-hydraulics modeling, chemical reaction engineering, electrochemical systems, system analysis, and advanced energy conversion systems
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candidates will engage in programs involving expertise in thermal-hydraulics modeling, chemical reaction engineering, electrochemical systems, system analysis, and advanced energy conversion systems
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researchers performing molecular modeling and machine learning activities. The candidate will be expected to perform ion conductivity experiments with thin film polymer electrolytes. The candidate will use
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candidate will be supporting is also heavily engaged in the study of energy storage systems, grid decarbonization, and electricity markets. The position will involve the development and use of computer models
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of experimental laboratory work with a variety of electrochemical based methods (galvanostatic/potentiostatic, AC impedance, and hybrid potential/current control methods) coupled to surface