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to quantify the impacts of new component technologies, control algorithms and powertrain architectures with focus on advanced technologies. The candidate will assist on projects to benchmark next generation
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Manufacturing group perform science-based membrane synthesis and scaleup development by using roll-to-roll manufacturing and machine learning enabled in-line characterization and quality control methods
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candidate will develop a novel multiscale multimodal experimental apparatus with precise control during data acquisition, as well as work on data processing pipeline, adaptable to imaging of energy-conversion
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and lanthanides within controlled atmosphere gloveboxes. Apply chemical thermodynamic and kinetic theories to understand processes and develop models of material interactions and behavior in molten salt
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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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(CSTR), with control over morphology, particle size, and composition Conduct physical, chemical, thermal, and electrochemical characterization of layered oxide cathode materials using a range of
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considerable amount of 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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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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the development of AI models for robotic control and the demonstration of these methods via simulation and experiment. Beyond the listed projects, the candidate may contribute to other large-team scientific
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acquisition, instrument control, and data analysis in Python or similar languages Knowledge of quantum optics measurements such as photon correlation functions or photon-number-resolved detection Familiarity