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programming and applied mathematics, and interested in neural networks and their hardware implementation. Some experience in machine learning would be an asset. Prior knowledge of emerging memory
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significantly advanced grasp synthesis in simulation, deploying these models onto physical hardware remains a critical bottleneck. End-to-end learning methods often require prohibitively large datasets
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: Master's (M2) or engineering-school student in machine learning, applied mathematics or computer science Strong linear algebra; probability and optimization are a plus Solid Python and PyTorch Care in
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