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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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engineering, controls and data systems, and internal and external scientific partners. Essential Duties and Responsibilities: Lead preparation of a review-ready engineering specifications document
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computational as well as experimental laboratory work with a variety of electrochemical based methods (galvanostatic/potentiostatic, AC impedance, and hybrid potential/current control methods) coupled
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(HPC) environments and large-scale data management. Experience with version control (e.g., Git) and collaborative software development practices. Experience with real-time analysis and instrument control
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of beam dynamics, beginning with macroscopic beam control (e.g., centroid and beam size) and advancing to techniques that enhance high-power, high-frequency radiation generation via wakefield production—a
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experiment tasks, implementing the infrastructure that handles message exchange and tool calls, and devising tools that control beamline instruments and launch simulations/analyses. You will help integrate
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on developing a new hybrid light–matter platform that couples transition metal complexes with optical microcavities to achieve optical control over ultrafast spin conversion and charge transfer
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technologies, control algorithms and powertrain architectures with focus on advanced technologies. The candidate will assist on projects to benchmark next generation vehicle systems, identify opportunities
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components. Work closely with a beam diagnostics physicist and controls group engineer to install and optimize diagnostic systems. Develop and integrate mmWave diagnostics equipment for beam position
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harness the nonequilibrium correlation between structural, charge, and spin/pseudospin degrees of freedom in two-dimensional (2D) materials. The success of this program will lead to new means to control