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, their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the newly established Chair of Algorithmic and Structural Graph
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to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, thenewly established Chair of Algorithmic and Structural Graph Theory offers a position as
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federated knowledge graph framework that facilitates the querying, consolidation, analysis, and interpretation of distributed proteomics-focused clinical knowledge graphs. To achieve this, we will employ
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, complex datasets from multiple sources Integrate and harmonize data using semantic data linking (ontologies/knowledge graphs) to create decision-ready information Design and prototype scalable workflows
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the ANR. PhD student in Graph Signal Processing for the Characterization of Multipolar Electrograms of Persistent Atrial Fibrillation. Responsible for a significant proportion of brain strokes, atrial
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and interdisciplinary data integration develop new AI-based methods, tools, scripts, ontologies and a knowledge graph based on RTG research results and relevant literature provide methodological support
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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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graph using RDF, OWL, and related technologies Designing and implementing workflows for data ingestion, integration, and querying across multiple systems Driving use-case studies that demonstrate
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) Research area: Large Language Models (LLMs), knowledge graphs (KGs), commonsense knowledge Tasks: foundational or applied research in at least one of the following areas: LLMs, KGs, knowledge extraction
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shifts in cell state and cell fate. Integrate spatial transcriptomics data to anchor these predictions in tissue context. Develop machine learning methods (e.g. graph neural networks, variational