Uncertainty Quantification and Statistical Learning

Welcome to the Chair of Uncertainty Quantification and Statistical Learning! The group's research interests broadly lie at the intersection of machine learning and traditional statistical methods. The topics, we are working on, include: Big Data Methods, Bayesian Computational Methods, Bayesian Deep Learning, Machine Learning, Copula Modelling and Regression Copulas, Distributional Regression, Network Analysis, Smoothing, Regularization and Shrinkage as well as Spatial Statistics.

We are co-affiliated with the Department of Statistics at TU Dortmund. For further Information regarding our team, research and teaching please visit our group's website. Follow us on Twitter and take a look at Prof. Klein's Google scholar page.

We are currently looking for PhDs or Post-Docs in our lab. If you are interested in joining the lab you can find more information here. In addition, we are looking for a student assistant, see here for more information.