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Field
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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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of continual graph learning. Continual graph learning studies how graph neural networks can learn from a sequence of evolving tasks, graphs, or distributions while retaining previously acquired knowledges
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thesis in the field of continual graph learning. Continual graph learning studies how graph neural networks can learn from a sequence of evolving tasks, graphs, or distributions while retaining previously
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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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graphs and network medicine • Translational data science for therapeutic discovery Primary Responsibilities: The Postdoctoral Research Associate is expected to lead and contribute to independent and
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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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deep-learning and 3D computer-vision models that detect features while representing a distribution of plausible interpretations. Encode geological relationships in a knowledge graph that stores
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develop knowledge-grounded reasoning methods that connect salient nucleotides, motifs, genes and regulatory elements to biological annotations, ontologies, knowledge graphs and literature-derived evidence
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-agent systems b. Mapping and Scene Representations - Dynamic Scene Graphs modelling uncertainty - Unified situational awareness for multi-robot systems in large and degraded environments Qualifications
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of coronary anatomy from 2D X-ray angiography; develop physics-informed neural networks and graph-based neural operators for fast estimation of 3D coronary hemodynamics (velocity, pressure, and wall shear