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, semantic modelling, ontology engineering, formal logics or cognitive modelling, and some experience with linked data standards and knowledge graph tools (e.g., RDF, OWL, SHACL); familiarity with or interest
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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 gold standard of geo
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-driven taxonomy; 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
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of the following: static and/or dynamic program analysis, programming language techniques (such as semantics, type systems, runtime systems, etc), formal verification, or software engineering
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-water settings. The research will develop a unified framework that fuses heterogeneous sensing modalities through uncertainty-aware probabilistic optimization while maintaining semantic, structural, and
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, Computer science, Ontology engineering, Computational geoscience, AI and NLP, or a related field; a strong interest in conceptual modelling, semantic modelling, ontology engineering, formal logics or cognitive
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— localization and mapping (e.g., SLAM), motion planning, and semantic perception — focusing on multimodal sensor data fusion (LiDAR, RGB-D, IMUs) for robust real-world performance. Research areas include