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17 Apr 2026 Job Information Organisation/Company University of Twente (UT) Research Field Computer science » Informatics Computer science » Programming Philosophy » Philosophy of science Researcher
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semantic harmonisation and retrieval Designing and implementing Retrieval-Augmented Generation pipelines that combine structured clinical data with unstructured text and external knowledge sources Designing
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of the University of Twente: Semantics, Cybersecurity and Services section within the Faculty of Electrical Engineering, Mathematics and Computer Science; Financial Engineering and Business Information Systems and
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of the University of Twente: Semantics, Cybersecurity and Services section within the Faculty of Electrical Engineering, Mathematics and Computer Science; Financial Engineering and Business Information Systems and
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fragmentation. This project seeks to overcome these barriers by integrating BIM-based energy modeling, semantic data models (Ontologies), and Large Language Models (LLM) into the control workflow. The candidate
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 12 days ago
and fine-grained semantic information within the prompts, and assess geometric accuracy of corresponding models' answers. If necessary, we will then propose dedicated learning strategies for inducing
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 days ago
. This would enable semantics-preserving, collaborative data platforms for decentralized graph-relational ecosystems. Objectives of the PhD The overarching goal of this PhD is to establish the theoretical and
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communications see our review paper entitled “Semantic Communications in Networked Systems: A Data Significance Perspective” published in IEEE Network, vol. 36, July/August 2022. The project is part of a
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would be happy to discuss PhD projects related to these aims, as there is some flexibility in research directions. Characterise behaviourally-relevant visual and semantic dimensions by the use of large
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation