The Project is concerned with Machine Learning and probabilistic modeling applied to proteomics experiments. Methodologically, this project will be focused on advanced unsupervised methods for computational inference such as Factor analysis, and autoencoding Deep Neural Networks, as well as the implementation of such methods on modern high-performance computers and clusters. [More]

Originally posted on 2017-12-12