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Field
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the available funding. Eligibility criteria Capacidad para programar sistemas embebidos y diseño digital en HW basado en FPGA Ability to program embedded systems and digital design in FPGA-based hardware
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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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simulations on superconducting processors for physics, chemistry, and computer science. Firmware development & programming tools to interface with FPGA-based electronics. Quantum verification and validation
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diseño y verificación con FPGAs. Experiencia demostrable en el diseño de sistema empotrados de alto rendimiento para aplicaciones de aprendizaje automático (ML/DL) aplicado a imágenes. Experiencia
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-healthcare technologies•Security and privacy in computing systems and IoT•Intelligent wireless communications and networks•Systems-on-chip, FPGA/microcontroller design, real-time systems•Biomedical
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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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optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution
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significant prior experience of: power semiconductor switching converters such as oscilloscopes programming MicroSemi FPGAs in the Libero environment low level programming of embedded C++ in Infineon Tricore
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Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
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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