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18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Post-doc on formal verification and algorithm discovery for numerical analysis About us and
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optimization for heterogeneous distributed data, and hardware/software codesigned engines for demanding applications. Main duties and responsibilities Work closely with all members of the lab carrying out
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, and model adaptation strategies. Scalable AI training: distributed training, efficient fine-tuning, evaluation, and deployment on large-scale compute. Multimodal learning: representation learning and
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quantitative and probabilistic extensions, and scalable verification via symbolic automata and related decision procedures Routing algebras: composable, algebraic representations of distributed
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incorporate the known design information into the imaging process? The primary focus will be on algorithm development, followed by their demonstration at synchrotron experiments. You will start
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? The primary focus will be on algorithm development, followed by their demonstration at synchrotron experiments. You will start working with an existing data acquisition and reconstruction pipeline
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networks, including 6G, WiFi, and satellite systems, support robust perception and inference for distributed AI agents, and how the realities of networked operation shape the design of adaptive
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18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc in ML-Based Co-Design at EPFL Mission The EPFL computer vision lab ( https
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https