Three Postdoctoral Researchers in Bayesian Machine Learning
Three positions are available in the following project of PI’s Prof. Aki Vehtari (Aalto University), Prof. Antti Honkela and Prof. Arto. Klami (University of Helsinki). We will develop theory and methods for assessing the quality of distributional approximations based on leave-one-out cross-validation and projection predictive model reductions, and seek to improve the inference accuracy by targeting the approximation towards the eventual application goal and by better utilising the available data, e.g., when having data with privacy constraints. To guarantee wide applicability of the project results in data science industry and academic research, the novel methods will be evaluated on a range of practical machine learning models and implemented as part of the leading open-source probabilistic programming systems. The project includes several research visits to Columbia University, New York (Prof. Andrew Gelman), Cambridge University, UK (Prof. Zoubin Ghahramani), Technical University of Denmark (Prof. Ole Winther).
The review of the position will begin on Nov 1, 2017 and the position will remain open until filled. For further information, please visit here.