In partnership with Sony CSL Barcelona, we invite applications for a fully funded 3 year PhD Position, starting in November 2025, on the topic of
"Predicting the evolution of scientific knowledge: exploiting knowledge graphs and ontology embeddings" Application Deadline: Apply before June 11, 2025 A more detailed topic description is below. The PhD project is coordinated by Prof. Oliver Kutz and Prof. Diego Calvanese at the Free University of Bozen-Bolzano (Italy), and by Dr. Tarek Besold at Sony CSL (Barcelona, Spain). The successful applicant is expected to spend two extended 6 months periods in the Sony Lab Barcelona, with main PhD studies pursued in Bolzano within the world-renowned KRDB Research Centre for Knowledge Based Artificial Intelligence. https://www.inf.unibz.it/krdb/ Full details about the PhD program in Computer Science at the Free University of Bozen-Bolzano and the application procedure are at the following link: https://www.unibz.it/en/faculties/engineering/phd-computer-science/ Topic Description: In partnership with Sony CSL, we invite applications for a PhD position in graph-based machine learning and semantic modeling. The PhD project is set up in collaboration with Sony's "AI for Scientific Discovery" team and will address AI/ML topics relating to the literature-based prediction of novel scientific insights, spanning from theoretical questions related to the use of knowledge graphs and ontology embeddings in ML models to the application of the resulting methods in high-impact real-world applications from the life sciences. Topics can connect to one or several of the following themes: * Extracting and representing multi-modal information (concepts and their relationships, experimental quantitative data, figures/graphs...) from scientific publications * Modeling scientific knowledge and its evolution over time in expressive knowledge graphs * Integrating semantic information (e.g., through ontologies) in ML models * Developing high-accuracy link prediction and edge classification models over temporal sequences of expressive knowledge graphs Required mandatory skills: The PhD topic resides at the intersection of machine learning, knowledge representation and reasoning, and semantic technologies. The candidate has undertaken machine learning and knowledge representation courses with proficiency. Ideally, the MSc thesis is in the field of graph neural networks, neurosymbolic integration, or knowledge-informed machine learning. Solid programming skills in Python and experience with PyTorch are required. Desirable (optional) skills: Previous experience with knowledge graphs and ontologies is a strong plus. Familiarity with the field of biomedical science as prospective application domain is a strong plus. Previous experience with software engineering is a plus. Ideally, the MSc thesis has led or will lead to a publication. For inquiries, contact: Oliver Kutz oliver.k...@unibz.it<mailto:oliver.k...@unibz.it> -- [LOGIC] mailing list, provided by DLMPST More information (including information about subscription management) can be found here: http://dlmpst.org/pages/logic-list.php
