PhD Fellow in knowledge-driven machine learning | Tromsø, Troms, Norway | The Arctic University of Norway

Position:	PhD Fellow in knowledge-driven machine learning
Institution:	The Arctic University of Norway
Location:	Tromsø, Troms, Norway
Duties:	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
Requirements:	This position requires a master's degree in physics, mathematics/statistics, computer science, or similar, or a corresponding foreign master's degree recognized as equivalent to a Norwegian master's degree.  If you are near completion of your master’s degree, you may still apply. You must document significant coursework in machine learning, pattern recognition, statistics, deep learning, and programming skills. Coursework in signal processing and physics will be considered a plus.

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