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, such as programming, documentation, and vulnerability detection, their adoption for other tasks such as software architecture design, or safety and hazard analysis, is still limited. The objective
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performance. The research focuses include: runtime-reconfigurable neural network software kernels for novel embedded systems architecture, performance models for adaptive AI workloads, on-device search and
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clusters with low power consumption and ultra-low and deterministic latency. The focus of the PhD activity is on demonstrating disruptive new network architectures for AI compute clusters utilizing optical
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packaging, where EISLAB is responsible for the packaging part within a European consortium. Subject description Cyber-Physical Systems focuses on integrated software and application architectures with
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responsible for the packaging part within a European consortium. Subject description Cyber-Physical Systems focuses on integrated software and application architectures with implementations of massively
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, advanced packaging, backside power delivery networks, and chiplet-based architectures require new methodologies to model and optimize system behaviour beyond the traditional chip boundary. You will develop
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and bottlenecks, as well as communication requirements. Develop and evaluate quantum computing hardware and software architectures that benefit from the idea of modular, interconnected and possibly
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neural networks (GNNs), transformer architectures, foundation models, and large language models (LLMs). Experience developing reproducible biomedical software and AI workflows. Demonstrated success
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are essential. Experience with finite element simulation software will also be considered an asset. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7315-DAMAND-007/Default.aspx Requirements
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or hard constraints, operational bounds (voltage limits, capacity, phase balance), and network topology through graph neural network architectures. You will build validated benchmark datasets and an