The newly founded Institute for Statistics and Foundations of Machine Learning at TU Braunschweig is looking for applicants for a PhD position in the field of Statistical Learning Theory to be filled as soon as possible. 

The research area focuses on Statistical Learning Theory, studying the mathematical foundations of learning from data. Central topics include generalization, stability, regularization, and optimal convergence rates of modern learning algorithms such as kernel methods and neural networks, with provable guarantees under finite-sample and high-dimensional settings.

The PhD project is positioned at the interface of learning theory and applied mechanics. It develops and analyzes learning-based methods for mechanical systems governed by nonlinear PDEs, using physics-informed approaches as a structured modeling framework. The emphasis lies on theoretical understanding and generalization properties of these methods.

Required background: Master’s degree in mathematics, statistics, machine learning, or a closely related field