Phd/doctoral Tromsø, Norway Apply
Job
UiT The Arctic University of Norway
Machine Learning Group, Dept. of Physics and Technology
PO Box 6050 Stakkevollan
9037 Tromsø
Norway
The address could not be found.

Join Integreat, a Norwegian centre of excellence with a community of ambitious researchers from the fields of machine learning, statistics, logic, language technology, and ethics. Integreat, the Norwegian centre for knowledge-driven machine learning, is seeking to recruit a fulltime PhD student at the UiT The Arctic University of Norway for a cross-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.

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 relationship graphs may vary in number of nodes and edges, and additionally have labelled nodes, which makes comparison of such graphs very challenging. Furthermore, we want to incorporate knowledge of an underlying semantic relationship between the nodes of the graphs, independent of the extracted spatial graphs themselves which should be integrated using suitable representations and embeddings.


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Contact Person
Dr. Elisabeth Wetzer