PhD student position in information-theoretic generalization bounds at the Department of Electrical Engineering at Chalmers University of Technology.

About the position

Machine learning algorithms are a crucial component of the data-scientist toolbox. However, the empirical success of modern machine-learning algorithms is still a puzzle to theoreticians. The goal of this PhD project is to use tools from information theory i) to explain why modern machine-learning algorithms perform so well and ii) to guide their design. Additional information on the project are available here.

The selected candidate, who will be jointly supervised by Prof. Giuseppe Durisi at the Department of Electrical Engineering, and Prof. Rebecka Jörnsten at the Department of Mathematical Sciences, will be part of a large network of junior and senior researchers at Chalmers performing research in theoretical machine learning.


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