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, semantic modelling, ontology engineering, formal logics or cognitive modelling, and some experience with linked data standards and knowledge graph tools (e.g., RDF, OWL, SHACL); familiarity with or interest
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learning, etc.); · Knowledge of explainable AI and Knowledge Graphs with ontology (e.g., RDFS, OWL); · Demonstrated experience with common advanced signal processing techniques (e.g. denoising
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Integrate extracted information into biodiversity data infrastructures (e.g. DiSSCo, GBIF, Disentis Libroscope), ensuring alignment with FAIR data principles and compatibility with common formats (e.g. RDF
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modelling, and some experience with linked data standards and knowledge graph tools (e.g., RDF, OWL, SHACL); familiarity with or interest for GIS, cartographic maps, geodata infrastructures and geo-analytical
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ontology alignment in physics and materials domains Build and maintain ontologies, OWL/RDF knowledge graphs, SPARQL endpoints, and open benchmarking suites to guarantee FAIR, reusable research data Mine and