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paradigm shift in the processing, semantic enrichment, representation, exploration, and study of historical media across modalities, time, languages, and national borders. To complete our team in Luxembourg
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contributing to the integration of ontologies, knowledge graphs, and related semantic web technologies into this architecture. The final aim is to demonstrate how this integration augments the development
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collaboration, and who have experience in the following areas (with the first being the most important): Semantic web technologies and knowledge graphs (RDF, SPARQL, SHACL, etc.) Large language models (LLMs
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, Impresso - Media Monitoring of the Past (https://impresso-project.ch/ ) is an interdisciplinary research project that uses machine learning to pursue a paradigm shift in the processing, semantic enrichment
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on (graph) clustering algorithms that should help to formally define relationships between semantically linked structures and thus offer insight into the structure of the textual source. The next highly
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skills (e.g., Python, R) and familiarity with semantic web technologies (e.g., RDF, OWL). A good collaborator and listener, with a questioning mindset. Excellent attention to detail. Ability to think