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. Prior exposure to hybrid analog-digital beamforming architectures. 9. Knowledge of FPGA or GPU-based signal-processing platforms. 10. Experience in THz or sub-mm-wave measurement setups
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. Familiarity and understanding of microwave and RF measurement circuit elements and instruments Familiarity with Field Programmable Gate Array (FPGA) operation and coding Skills Needed: Knowledge, understanding
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, single-atom catalysts), analytical instrumentation (including electronics and LabVIEW FPGA programming), finite element modelling using COMSOL Multiphysics, and in-situ/operando spectroscopy, among other
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signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis
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implementations on deeply embedded platforms FPGA development, including test and verification Schematic entry and PCB Layout using Altium Designer ECAD/MCAD co-design using Solidworks ARM Cortex M 32-bit
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Experience with analog and digital electronics, FPGA programming, including writing firmware and software for microprocessors and embedded systems would be considered an asset. Condition of Employment
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hardware design (Verilog/VHDL), FPGA-based acceleration, etc. Experience with deep learning frameworks like PyTorch, Keras, or TensorFlow, and tools such as Jupyter Notebook, is expected. A strong foundation
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into the co-design of ultra-low-power AI hardware architectures tailored for edge computing applications. The research aims to develop neuromorphic processors, FPGA/ASIC-based AI accelerators, and intelligent
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, especially precision/high sensitivity circuits (e.g. low current design). Experience writing software to run embedded systems – ideally FPGA code, but microcontroller also very welcome. Good communication
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., GNURadio, Matlab, LabView), and/or FPGA development (e.g., VHDL) is a plus. You are a team player and have strong communication skills. You have a high proficiency in oral and written English. You comply