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language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g., Git) Interest in or experience with semantic web
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semantic querying and reasoning over materials-science/physics corpora Developing pipelines for semantic enrichment of unstructured data, including entity recognition, relation extraction, and automatic
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PhD: Semantic Modelling of Geodata Sources and Geo-analytical Workflows Faculty: Faculty of Geosciences Department: Department of Human Geography and Spatial Planning Hours per week: 36 to 40
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; develop a hybrid question parsing pipeline using NLP and formal semantic representations; investigate Large Language Models (LLMs) as well as symbolic AI for question parsing; evaluate models based on a
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candidate for this position holds an MA/MSc-degree or equivalent with a focus on Linguistics, and above-average qualifications, has strong familiarity with formal semantics and pragmatics, and excellent
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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve
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, or willingness to work with them Experience with multi-modal machine learning methods Familiarity with formal linguistics, particularly formal semantics and pragmatics We encourage applications from individuals
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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? What are the elements of meaning (image ciphers) that make up the semantic field of images? To what extent can images be precisely determined in their semantic content? Such questions need to be explored
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, Google.org, SAP, Merck, TUM Klinikum, Holtzbrinck). Diverse research topics and technologies, including: Conversational Semantic Search, Question Answering Systems, Complex Information Extraction. Fact