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description (e.g., using SystemVerilog, or VHDL) The members of the evaluation panel assigns a classification to each of the candidates on a scale of 0 to 100 points, ranking the candidates according
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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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