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which are transferable to electronic LabBooks and data platforms of relevance for other researchers within the MaterialVital Hub. Lead the development of ELM-dedicated ontology for interoperability within
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framework for AI in gynecological oncology. We integrate symbolic knowledge representation (Ontologies/Knowledge Graphs) with Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to create
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ontologies and knowledge bases and their population with textual and sensor data Development of methods for the automatic quality assurance of heterogenous data Development of interactive assistants based
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methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems. Candidates
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area Proven experience of semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS, OWL Proven experience with predictive and generative AI Practical experience in using
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knowledge graphs, ontologies, data modelling, RDF, RDFS, OWL Proven experience with predictive and generative AI Practical experience in using large language models, generative AI techniques, prompt
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are often associated with bodies of water (seas, oceans, rivers, and deltas). They can move, change shape, and transcend political and ontological boundaries. This postdoctoral research fellow will, as part