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Mathematical Researcher Position

2 weeks ago


Umeå, Västerbotten, Sweden TN Sweden Full time

About the Project

Project Overview

Machine learning, a subfield of artificial intelligence, is revolutionizing various aspects of society and research. This impact is expected to increase further with the development of deep neural networks, a class of powerful machine learning models.

This project aims to contribute to the theoretical understanding of the empirical success of deep neural networks, specifically within the subfield of geometric deep learning. Geometric deep learning concerns symmetries in data or learning tasks and constructing neural networks that react properly to them.

The project will focus on developing new ways of constructing equivariant networks, describing the resulting models mathematically, and analyzing how symmetries affect the training of neural networks.