As a member of a computational biology group at the German Cancer Research Center (DKFZ) you will develop new statistical or computational methods to analyze high-throughput biological data. The group works on quantitative analysis of genetic and physical interaction networks. Statistics and computational network analysis will be used to predict and understand interactions between genes, proteins and drugs in various ways with the aim to guide targeted drug therapies. The group will further develop methods that integrate available population level genetic data with experimental data. The candidate is expected to work in close collaboration with experimental scientists at DKFZ and other institutes in Heidelberg.
The successful candidate will explore the interplay between the transcriptome and the proteome. In recent years hundreds of novel proteins have been identified that have the ability to bind to RNA (Castello, Fischer, Cell, 2012). New approaches to study the mRNA-target of proteins (HITS-CLIP) and newly transcribed proteins (Ribo-profiling) make use of next-generation sequencing. The successful candidate is expected to develop methods for the quantitative analysis of next generation sequencing data in the context of HITS-CLIP and Ribo-profiling.
The ideal candidate will have a master’s degree in computer science, Mathematics, Physics, or Biological Sciences with a strong background in bioinformatics and/or statistics. Programming skills are desired. Knowledge in R-programming and analysis of genomics or other genomics data are of advantage. The candidate should have the ability to work in interdisciplinary teams.
Application should be send via the DKFZ-job portal that you can find here:
Informal inquiries can be send to Bernd Fischer.