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candidate will focus on developing terahertz cavity-magnonics platforms based on low-damping antiferromagnetic oxides, with an emphasis on controlling and coupling antiferromagnetic spin excitations using
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to the design, fabrication, and characterization of superconducting devices based on high kinetic inductance materials. This position offers a unique opportunity to help build a new research capability with
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separations in controlled environments such as radiological hoods, gloveboxes, and hot cells Design, assemble, operate, troubleshoot, test, and optimize experimental systems and specialized apparatus, including
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experiments with active load control and interpreting the resulting microstructural evolution. Experience studying corrosion effects on materials relevant to nuclear systems. Experience with advanced materials
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technical reports Contribute to integration of instrumentation, controls, and data acquisition systems for experimental platforms Work with aqueous and organic chemical systems and support characterization
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or robotic systems Knowledge of system integration, instrument control, workflow automation, and data acquisition Experience developing and applying AI/ML methods, including predictive modeling, active
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. The candidate will work closely with computational modeling collaborators to validate reactor designs and optimize operating parameters. The candidate will be expected to contribute to report preparation
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, battery electric and fuel cell powertrain design, development of supervisory control logic, validation of vehicle models against test data etc. The projects and interests of this group span all modes
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methods for analysis, tuning, and control of particle beams and accelerator systems, with applications to the APS injector and the newly-upgraded APS storage ring. This work will explore applications
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techniques to industrial energy systems, manufacturing systems, and commodity supply chains. Integrate data-driven methods with optimization-based modeling frameworks, including linear, mixed-integer