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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 3 months ago
programming, machine learning (scikit-learn, PyTorch/TensorFlow), ontologies (OWL/RDF), and/or computational cognitive modelling Interest in interdisciplinary research at the interface of computer science
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area Proven experience of semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS, OWL Proven experience with predictive and generative AI Practical experience in using
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knowledge graphs, ontologies, data modelling, RDF, RDFS, OWL Proven experience with predictive and generative AI Practical experience in using large language models, generative AI techniques, prompt
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technologies such as RDF, XML, JSON-LD, and Linked Open Data (LOD), etc. Experience with data integration and API technologies such as RESTful API, GraphQL, Apache Camel, etc. Experience with data processing
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, simple local deploys, secrets management. Nice to have: Deep NLP experience (relation extraction, weak supervision, prompt/adapter tuning). Semantic KGs (RDF/OWL, Neo4j/graph tooling), ontology work, and
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investigation of social and cultural dynamics. Your tasks will be: Implementation of approaches for lifting (meta-)data into RDF and for integrating it into the GRAPHIA knowledge graph Adoption and evaluation
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. Proficiency in semantic data modelling, utilizing technologies such as RDF, XML, JSON-LD, and Linked Open Data (LOD), etc. Experience with data integration and API technologies such as RESTful API, GraphQL
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MARC, BibFrame, RDA/RDF, Dublin Core, MODS. Familiarity with emerging trends in library technology such as linked data in production and AI-assisted tools. Proven ability to translate technical
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ABRDs and RDFs (Resident Deans of First-Year Students), and meets bi-weekly with the RD cohort; participates in both formal and informal mentoring relationships among RDs; and engages in regular trainings
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Resident Deans, including both other ABRDs and RDFs (Resident Deans of First-Year Students), and meets bi-weekly with the RD cohort; participates in both formal and informal mentoring relationships among RDs