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rankings to generate semantically correct types and properties Validation using SHACL, SPARQL, or reasoning Prototypical implementation of a pipeline for transforming API data into JSON‑LD Evaluation with
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
, JSON, Python, SPARQL, and/or graph query languages such as Cypher, relational databases such as MySQL, PostgreSQL, SQLServer, Oracle, Triplestores, or other semantic technologies). Experience with
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Experience with knowledge graphs, graph databases, or semantic web technologies (e.g., RDF, SPARQL, Neo4j). Background in natural language processing, LLMs, or information extraction. Familiarity with XAI
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language), cloud technologies, and/or database technologies such as SQL, SPARQL, or similar. We know that applicants come with different strengths, so you don’t need to meet every requirement to be a strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 11 days ago
, transformation, standardization, harmonization, and analysis of legacy data stored in a variety of formats (e.g., OWL, RDF, JSON-LD, JSON, Python, SPARQL, and/or graph query languages such as Cypher, relational
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-on experience with RDF(S), OWL, SPARQL, SHACL, or comparable technologies, and understand how semantic models enhance interoperability. Explorative and innovative – You enjoy scouting new technologies, developing
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, the CIDOC CRM ontology and its extensions, SPARQL queries. • Experience with version control and dissemination tools: GitHub/GitLab, Zenodo. • Understanding of the European research project ecosystem
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, hybrid retrieval (BM25 + embeddings), graph databases (e.g., Neo4j), RDF/SPARQL, schema mapping, entity resolution. 3. Research Fit: Interest in applied research with real operational datasets. Motivation
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, hybrid retrieval (BM25 + embeddings), graph databases (e.g., Neo4j), RDF/SPARQL, schema mapping, entity resolution. 3. Research Fit: Interest in applied research with real operational datasets. Motivation
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representation languages such as RDF, OWL, SPARQL Experience with Semantic Web technologies, including graph databases (GraphDB, Neo4j), relevant libraries (RDFLib, owlready2) and other software (Protégé