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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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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
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Lupins (NWLs) and compare them with the mechanisms described for the Old World Lupins (OWLs). This research aims to understand flowering induction, vernalization response, and adaptation to changing
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pipelines for semantic enrichment of unstructured data, including entity recognition, relation extraction, and automatic ontology alignment in physics and materials domains Build and maintain ontologies, OWL
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experience with knowledge graph standards (e.g., RDF, OWL, SHACL); familiarity with GIS, geodata infrastructures and geo-analytical workflows some experience with AI and machine learning methods to label texts