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); execute PoCs and tech transfer with foundries, equipment/materials/metrology vendors. Data & Platforms: Establish robust data governance and MLOps pipelines; develop reusable algorithms and prototype
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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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the development of meta-optimization techniques that can automatically search for the best algorithm-hardware pair for a given problem. While we have a history of success in optimizing digital