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laude level. You are interested in both Machine Learning and Symbolic/Logic-based AI methods. You strive for excellence and have a scientific mindset. You are a loyal team player, who can work
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increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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), machine learning, advanced use of LLMs. Experience with Unix-like environments and software development in the context of large (open-source) software projects is highly valuable. The applicant should be
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to the development of digital twins of sloshing tanks and explore collective learning approaches where multiple systems share knowledge. The PhD will be carried out in joint collaboration between the Université Libre
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contribute to the development of digital twins of propellers and explore collective learning approaches, where multiple propellers cooperate for optimal flight control. The PhD will be carried out in joint
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. Kinetic rates will be calculated on the fly from molecular dynamics simulations using machine learning potentials. This approach will provide guidelines to steer the formation process of zeolites by tuning
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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information about the role, please contact Prof. Radu State Your profile Strong background in AI, machine learning, or multi-agent systems, ideally with interest in financial systems, decentralized ledgers