We seek a talented and motivated post-doc to develop computational methods for identifying regulatory genetic variants influencing the risk of common diseases. Research topics include: integration of rare and common regulatory effects on expression level and isoform choices, modeling of rare regulatory variants using deep learning based mechanistic models, and analysis of the role of cryptic splicing in common diseases. The developed methods will be applied to cardiovascular disorders in collaboration with Prof. Heribert Schunkert, Head of the German Heart Center, and to schizophrenia, in collaboration with Dr. Michael Ziller, group leader at the Max Planck Institute of Psychiatry.
The position is funded for 2 years. The salary is according to the TV-L (German academic salary scale).
Candidates must either hold a PhD in computational biology or bioinformatics, or hold a PhD in physics, statistics, or applied mathematics with practical experience in high-dimensional data analysis. Experience in quantitative genetics is a plus. Applicants must have a proven publication record and an interest for translational research.
The Gagneur lab is interested in how gene expression is encoded in genomes, and how to leverage this knowledge to understand the basis of genetic diseases. To this end, we employ statistical modeling of ‘omics data and work in close collaboration with experimentalists. Relevant recent work includes establishing RNA-sequencing as a powerful companion to genome sequencing for genetic diagnosis of Mendelian disorders , modeling of RNA metabolism from sequence [2, 3], and deep learning modeling of cis-regulatory elements .
We are located at the faculty of informatics of the Technical University of Munich. The TUM together with other excellent research institutions in Munich offer a dynamic, interactive and international research environment. With plenty of cultural attractions, green areas, and the proximity of the Alps, Munich provides a superb quality of life.
 Kremer et al. Genetic diagnosis of Mendelian disorders via RNA sequencing, Nature communications, 2017
 Eser. et al, Determinants of RNA metabolism in the S. genome, Mol. Syst. Biol., 2016
 Schwalb et al. TT-seq maps the human transient transcriptome, Science, 2016
 Avsec et al., CONCISE: Convolutional Neural network for CIS-regulatory Elements, https://github.com/gagneurlab/concise and http://www.biorxiv.org/content/early/2017/07/18/165183
HOW TO APPLY
Associate professor of Computatonal Biology
Faculty of Informatics
Technical University of Munich