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collaboration, and who have experience in the following areas (with the first being the most important): Semantic web technologies and knowledge graphs (RDF, SPARQL, SHACL, etc.) Large language models (LLMs
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enrich experimental data from omic analyses into queryable knowledge graphs. This work will rely on semantic standards (RDF, OWL, SPARQL, SHACL) and will integrate techniques for automatic annotation and
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(usually acquired by attending a course on advanced databases or database systems implementation) Experience with graph databases (RDF or Property Graphs) Experience in handling streaming data Personal
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I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
, data-science (e.g., neural networks, deep learning, autoencoders, GANs, active learning, etc.); · Knowledge of explainable AI and Knowledge Graphs with ontology (e.g., RDFS, OWL
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of database systems internals (usually acquired by attending a course on advanced databases or database systems implementation) Experience with graph databases (RDF or Property Graphs) Experience in handling