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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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, including backend services, APIs, and databases. Hands-on experience integrating Large Language Models, RAG pipelines, embeddings/semantic search, and AI agents into working systems. Experience with cloud
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and table selection; SQL generation and execution; semantic filtering and information extraction; entity matching and data integration; aggregation, verification, and result explanation. For software
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Department of Philosophy, Linguistics, and Theory of Science, University of Gothenburg | Sweden | 14 days ago
2 Sep 2026 Job Information Organisation/Company Department of Philosophy, Linguistics, and Theory of Science, University of Gothenburg Research Field Language sciences » Linguistics Researcher
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; requires deep job knowledge of area typically obtained through higher education combined with experience. Manages large projects or processes and problems faced are difficult and often complex; analyzes
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. They will oversee the design and delivery of semantic models, dashboards and strategic reports, ensuring the provision of accurate, timely and trusted management information across the University. This is an
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28 Jul 2026 Job Information Organisation/Company CNRS-LIRMM Department Computer Science Department Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1
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execute privacy-sensitive tasks while preventing context leakage, state exposure, or unintended information flow through semantic side channels. The research will be validated through real-world use cases
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Compensation: - Benefits: For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/ Shift: First Shift (United States of America) Temporary or Regular
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Chair and Institute of Man-Machine Interaction | Aachen, Nordrhein Westfalen | Germany | about 2 months ago
combination of multimodal large language models and vision-language models with tool-specific knowledge via Retrieval-Augmented Generation, hybrid semantic search, embeddings, and vector databases. This is