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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team
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Monitoring Drift Chambers (MDT), and in the Event Filter track trigger (EFTracking). The group applies novel Machine Learning tools and techniques to both analyses and trigger upgrades, and leverages FPGA and
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detectors, ultra-high vacuum, tritium gas handling, magnetometry, cryogenic engineering, charged-particle trapping, atom trapping and cooling, RF/microwave cavities and radiation detection, FPGAs, Python, C
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associated cryogenic/RF electronics (e.g., cryo-LNAs, mixers, VNAs, spectrum analyzers), FPGA-based readout, or systems such as ROACH, RFSoC, etc.. Familiarity with EPICS, Bluesky, and beamline controls