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models embodied in agents, robots and digital twins, integrating explainability, traceability, bias auditing and compliance with the AI Act. Where to apply Website https://investigacion.ugr.es/recursos
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interactive models embodied in agents, robots and digital twins, integrating explainability, traceability, bias auditing and compliance with the AI Act. Where to apply Website https://investigacion.ugr.es
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safety. Activities will include the development and evaluation of pipelines for document extraction and semantic indexing, RAG systems and knowledge graphs, the integration and evaluation of Large Language
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of evaluation software, (2) validation of knowledge graphs, (3) evaluation of language models with RAG oriented to knowledge graphs. Where to apply E-mail [email protected] Requirements Research
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
: the even bicolor Wang tilesets. Preprint, 2025 [3] Hoyrup. Local generation of languages. Preprint, 2026. [4] Hoyrup. When a graph generates its own colorings. Preprint, 2026. Where to apply Website https
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for analyzing 3D data and automatically detecting objects and changes in the environments under study. Within this project, GREYC proposes to introduce new multi-scale graph-based representations adapted
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Framework Programme? Horizon Europe Is the Job related to staff position within a Research Infrastructure? No Offer Description Research on Knowledge Graphs, graph-based retrieval and trustworthy generative
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 1 Postdoctoral Researcher position in the line of research: "Ontologies and knowledge graphs for semantic
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properties are proved, refuted by counterexample, or reported as an explainable gap. All of it is written in a domain-specific language whose syntax trees and graphs we keep in a projectional editor (JetBrains
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 10 days ago
transformed into heterogeneous graphs, where rows become nodes and primary–foreign key relationships induce edges. GNNs can then propagate information across the relational structure and learn predictive