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and decoding information from neurons Prior experience dealing with custom hardware, FPGAs, and using/writing APIs to communicate with the hardware Like to live in the intersection of biology, hardware
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exposing hardware accelerators, such as GPUs and FPGAs, in a seamless and portable way. This includes designing execution logic and resource-scheduling strategies that make efficient use of available
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hardware design and verification (HDL: VHDL/Verilog, simulation tools). · Hands-on experience with FPGA prototyping or hardware/software co-design is highly desirable. · Good communication
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optics, ideally, knowledge of electronics, Python and FPGA (VHDL) programming, interest in working with experts on a cross-institute collaboration project, very good written and spoken English language
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models is desired - Experience with detector (Geant4) and electronics simulation would be beneficial - Experience with FPGA firmware development and familiarity with trigger systems would be beneficial
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tasks across distributed infrastructures. A key aspect of the position involves integrating and exposing hardware accelerators, such as GPUs and FPGAs, in a seamless and portable way. This includes
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platforms, including embedded and edge computing environments (e.g., Jetson, Raspberry Pi, FPGA, neuromorphic chips) Publish results in top-tier journals and present at leading international conferences and
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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
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architectures Support lab activities related to designing and optimizing AI implementations across various platforms, including embedded and edge computing environments (e.g., Jetson, Raspberry Pi, FPGA
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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