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on Leveraging Ontological Knowledge with Argumentative Agentic AI to Accelerate Chemical Development under the direction of Dr. Antonio Rago, in collaboration with Prof. Francesca Toni from Imperial College
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We invite you to apply for a 2-year postdoctoral position in the area of hybrid AI, combining modern language models (LMs) with ontologies and knowledge graphs (KGs). The position is part of a newly
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), SIMULATION (SCS/SAGE), Applied Ontology (IOS Press), and relevant IEEE/ACM journals. Prepare and present conference papers at CSER, INCOSE IS, CESUN, and similar venues. Contribute to technical reports and
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involve developing an approach that uses Knowledge Organization (KO) metadata and ontologies to optimize parallel processing and scheduling policies (via Kubernetes) for Machine Learning tasks. The fellow
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objective is to investigate how new technologies challenge moral values and ontological concepts (like “nature”, “human being” and “community”), and how these challenges necessitate a revision of these
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research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross
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academic and industrial partners across Europe. The project will develop materials ontologies, training-ready datasets, multi-modal knowledge graphs, and large-scale SciFM models, together with tools
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of the three positions is to contribute to the research fields on digitalisation and automation, with a particular focus on the development of an open and interoperable ontology for construction site processes
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and social sciences, and to position its consortium at the top of its field internationally. A key objective is to investigate how new technologies challenge moral values and ontological concepts (like
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datasets (e.g., RNA-Seq, epigenetics, cancer genomics, or metabolomics). Statistical Knowledge: Strong understanding of algorithmic, statistical, and ontological concepts in biology. Communication: Excellent