PhD Student Position in Mathematical Optimization for Learning at Lund University.

Mathematical optimization is an exciting and broad subject, covering both deep mathematics and hands-on implementation. It is a core component in many engineering fields, such as machine learning, signal processing, control, and image reconstruction. With the explosion of applications in the machine learning domain, optimization has never been more relevant.

The project is financed by the Mathematics for AI branch of the Wallenberg Autonomous System Program (WASP). The project focus is on optimization algorithms for machine learning, with one focus being saddle-point problems that appear, e.g., in training of Generative Adversarial Networks (GANs). The position includes participation in the WASP national graduate school on Math for AI, and with possibilities for longer international research visits abroad.

View all positons