27 Sep 2024

Norway

University UiT The Arctic University of Norway

Application Deadline December 10, 2024

Original Job Offer

PhD Fellow in knowledge-driven machine learning

Join Integreat, Norwegian centre of excellence with a community of ambitious researchers from the fields of machine learning, statistics, logic, language technology, and ethics. Integreat is the Norwegian Centre for Knowledge-Driven Machine Learning and is seeking to recruit a fulltime PhD student at UiT The Arctic University of Norway for across-disciplinary project across machine learning, statistics and logic, which is ambitious, timely, and contributing to a new foundation of machine learning.

About the position:

The position is for a period of four years. The nominal length of the PhD programme is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete research training to the level of a doctoral degree.

Admission to a PhD program is a prerequisite for employment. The workplace is at the Department of Physics and Technology at UiT in Tromsø. You must be able to start in the position in Tromsø within a reasonable time after receiving the offer.

Field of research and the role of the PhD Fellow

The focus of this PhD fellowship lies on method development in representation learning for graphs, similarity measures and clustering methods for graphs. Relationship graphs extracted from data have the potential to describe correlations and dependencies among objects in a dataset beyond pairwise interactions, and are crucial to quantify complex relationships in e.g., spatial omics. Generally, these graphs may vary in number of nodes and edges, and additionally carry labels on the nodes, which makes comparison of such graphs very challenging. In this project we want to find novel ways how to incorporate knowledge of underlying semantic relationships between these labels by means of representation learning, knowledge graph embeddings and exploiting non-Euclidean geometries to learn graph similarity measures.

We expect that you will engage in collaborative research with members of the machine learning group at UiT and the members of the Integreat community from both UiT, the University of Oslo, and the Norwegian Computing Centre. You will contribute to the centre’s seminars and be part of a network of young researchers in fundamental machine learning.