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Field
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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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. This project focuses on fundamental algorithmic questions on geometric networks and, in particular, on geometric intersection graphs: graphs whose nodes correspond to disks or other objects in the plane and that
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systems with "self-diagnosis" and "self-healing" capabilities. By integrating federated learning, graph neural networks, and blockchain technology, we will develop a framework that moves beyond static
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three coupled components. First, a physics-informed graph surrogate model will emulate network hydraulics at scale, representing pipes and assets as a graph and predicting flows, depths, surcharge
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ICT Services & Applications. Your role The SnT Automation & Robotics Research Group seeks to hire an excellent and motivated PhD candidate within the national research project PCS-GRAPHS (Integrating
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). "Statistical field theory applied to complex networks” "Quantum geometrogenesis – Graph theoretic approaches to building spacetime” web page For further details or to discuss alternative project arrangements
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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, and rigorously evaluate machine learning and deep learning models (CNNs, DNNs, transformers, graph neural networks, diffusion models, multimodal models, reinforcement learning) as well as software
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, learner-aware sequencing of content. This includes work on semantic parsing, structured NLP, graph-based neural models, metacognitive prompting, ontology alignment across disciplines, and human-in-the-loop
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of empowering citizens for the use of such technology. This work will be developed with the support of the interplay of Semantic Technologies (e.g., ontologies, knowledge graphs) and Artificial Intelligence