PhD Position in Computational Science and Engineering at UmeƄ University.

Project description
Artificial intelligence and deep neural networks have had tremendous success on several previously unsolved data analysis problems. The mathematical understanding of how and why deep neural networks work is however very limited. This project focuses on the development of mathematical methods and tools for investigation and future development of deep neural networks. In particular we will investigate the imposition of scale separation in deep neural networks for improved robustness and explainability.

This call is part of a joint call for doctoral students in Math/AI. It is done in several steps, where finding doctoral students is the second step. The first step, the project call, can be found here:

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