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background in Semantic Web technologies (RDF, OWL, SPARQL, SHACL) and ontology engineering methodologies and tools (e.g., Protégé). - Experience with Knowledge Graph architectures, graph databases
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, Machine Learning, or related areas. - Knowledge of Large Language Models and Retrieval-Augmented Generation. - Experience or interest in Knowledge Graphs, Semantic Web technologies, information retrieval
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of tax data. Core goals include creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools
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for the automatic detection of changes over time, semantic web technologies for the representation and enrichment of knowledge derived from this detection, and finally LLMs for querying the resulting knowledge bases
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
., Revenko, A., Teije, A. T., & Harmelen, F. V. (2023). Combining Machine Learning and Semantic Web: A Systematic Mapping Study. https://doi.org/10.1145/3586163 [2] Benoît Combemale, Pascale Vicat-Blanc
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pipelines for processing large-scale structured and unstructured datasets using machine learning, natural language processing, semantic search, and knowledge graph technologies. 2. Design, implement, optimize
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, and other enterprise analytics platforms. The incumbent develops trusted data products, enterprise semantic models, dashboards, AI-enabled analytics solutions, and self-service reporting capabilities
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, including WCAG 2.x, accessible HTML, keyboard navigation, semantic markup, color contrast, and accessible forms. Experience working with RESTful APIs, including understanding API structure, endpoints, HTTP
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here: https://itacademy.harvard.edu/ . Job Description Harvard Library and Harvard University IT are advancing the Reimagining Discovery initiative to transform how researchers, students, and the global
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information please see the Non-Discrimination Statement at the following web address: http://uhr.rutgers.edu/non-discrimination-statement