The candidate will develop and employ a variety of (deep) machine learning techniques, phylogenetic modeling as well as probabilistic Bayesian modelling to quantitatively characterize and predict pathogen recognition by the immune system and specifically in an autoimmune setting (celiac disease). Computational prediction of immune recognition is a long-standing computational and immunological problem. Improving computational methods for immune recognition is crucial for the development of personalized and precision medicine approaches such as next-generation infection, cancer and autoimmune (e.g. celiac disease) immunodiagnostics and immunotherapeutics. The candidate will also develop a software framework for fast and reliable processing of single-cell and proteomics immune cell omics data. The candidate will be expected to closely collaborate with machine learning experts, computational and experimental immunologists as well as clinicians.
Application deadline: 27 Feb 2019.