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, this PhD thesis will focus on the characterization of multipolar electrograms (EGM) through graph signal processing (GSP). The underlying hypothesis is that local propagation patterns in AF are associated
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knowledge graph from scientific papers and cognitive test questionnaire data, and second, to integrate the graph with transformer-based large language models and causal learning. This offers an explainable
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produce data that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models
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Can AI learn to reason like a human - and recognise when it isn’t sure? This PhD tackles that challenge in a high-impact setting: interpreting 3D digital models of rock formations built from drone
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(though not mandatory) if you have prior knowledge in ontologies, knowledge graphs, and/or robotics. You have demonstrated your excellent skills by outstanding grades during your bachelor's and master's
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for a PhD student to contribute to our growing activities. The RAI team is conducting fundamental research in all the aspects of robotics with a specific focus on aerial, space and bioinspired robotics
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Engineering is looking for a full-time (100%) doctoral scholarship holder in the field of Artificial Intelligence. Position You will work actively on the preparation and defence of a PhD thesis in the field
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the Faculty of Applied Engineering is looking for a full-time (100%) doctoral scholarship holder in the field of Artificial Intelligence. Position You will work actively on the preparation and defence of a PhD
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that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models for energy-system data
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-center clinical datasets and contribute to translating advanced computational methods into clinically relevant applications. This PhD position offers a unique opportunity to work at the intersection