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Field
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/chiplets/interposer/wafer-scale), quantum, superconducting, machine learning, edge computing, and security/privacy in computer architecture. Digital Logic Design and VLSI – including ASIC/FPGA design for
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design Signal Processing FPGA development Develop C/C++ or equivalent code to interface with developed hardware and associated interfaces (SPI, I2C, etc) Integration of Software Defined Radio (SDR
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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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board design or FPGA programming is a plus. Experience with automatic, semi-automatic probe-stations or manual probe measurement and notions on probe pad layouts and probecard design is a plus. You have
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can understand their limitations and take those into account in your design for test strategy. Experience with either PCB, demo board design or FPGA programming is a plus. Experience with automatic
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know the fundamentals of quantum computing. It is also expected that the participant has knowledge to work on diverse software and hardware (knowledge on working with FPGAs and ASICs will be preferred
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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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, 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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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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preferred; Hands- on experience in one of the following areas and desire to cross the boundaries and learn new things Embedded software development for the FPGA / CPU SoC systems (for example, Zynq 7000, Zynq