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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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. Nice to have: Practical experience with machine-learning frameworks (e.g., PyTorch). Prior tape-out experience (ASIC or a complex FPGA prototype) and familiarity with the digital back-end flow (synthesis
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, Computer Science, or related field with excellent grades. Sound knowledge of computer hardware design and synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication
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synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is an added
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design and synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is