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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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the early Eocene hyperthermals has so far not been constrained for shallow marine ecosystems. The goal of this PhD project is to assess the sensitivity of marine ecosystems in NW Europe to climate change
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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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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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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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. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ The selected candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with
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Number BAP-2025-545 Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD is part of the Marie Skłodowska-Curie Doctoral Network “MAGNIFY” and aims to tackle
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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
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to solve. In this PhD project, you will work on the characterisation of both spectrographs in the lab, and their commissioning at the observatory for MARVEL or in orbit after launch for CubeSpec. Furthermore