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The research groups of Wolfgang Huber at EMBL and Oliver Stegle at DKFZ and EMBL, located in Heidelberg, work on machine learning and statistical computing solutions for cutting-edge biology and biomedicine research. Their interdisciplinary teams engage in theoretical method development, translation into effective software, and scientific applications in collaboration with researchers from fields including cancer and developmental biology.

Your role

You will develop methods for finding low-dimensional explanations in high-dimensional biological data. Biological systems can now be studied at multiple levels (DNA sequence, chromatin plasticity, transcriptome, proteome, metabolome, imaging, etc.), increasingly at single-cell resolution. Such data, which often comprise millions of features per observational unit, have a wide range of important applications in basic biology and in biomedicine. You will be working on the most fundamental step in their analysis: finding and understanding the most important patterns. These can come in the form of latent factors, clusters, smooth manifolds, graphs, etc. The learning tasks comprise unsupervised, supervised and hybrid setups.

We are currently advertising two positions in this new and exciting field, with two complementary focus areas: (1) mathematical theory development and (2) development of high-quality scientific software and biological application in collaboration with domain experts.