---------- Forwarded message ---------
From: Oliver Kutz <[email protected]>
Date: Tue, May 13, 2025 at 5:00 PM
Subject: [AIxIA] PhD Position at Free University of Bozen-Bolzano, Italy,
in cooperation with Sony CSL, Barcelona.
To: AIxIA mailing list <[email protected]>



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
[email protected]


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