**Background** The last decade has seen a tremendous evolution in the field of clinical genetics. However, although new high-throughput DNA sequencing techniques have opened the door for routinely identifying genome variations that might contribute to a given disease, there are still several bottlenecks that stand in the way of widespread application in the clinic. Several of these issues can be (partly) solved with data visualization techniques. Geneticists rely heavily on genome browsers to investigate genetic variation in their genomic context (see e.g. http://www.ensembl.org and http://genome.ucsc.edu; visualization expert Ben Fry created http://bit.ly/lBK6wR). Although of priceless use, these browsers all have the significant drawback that they can only display data relative to a so-called "reference". It is also impossible for them to show rearranged chromosomes as they appear in for example cancer. **Aim** Within this project, we will build a new interactive genome browser that is capable of displaying so-called structural genomic variation and is able to display patient data relative to actual control (healthy) data rather than a theoretical reference. This visualization will include several features. First of all, it will be possible to visualize the differences in chromosome structure between individuals. This will be based on a directed graph, and might be inspired by the ABySS-Explorer tool by Nielsen et al (http://bit.ly/iZhLi1). Secondly, the tool will enable any path through this graph to be considered as the "reference", so that depictions resembling the genome browsers such as http://bit.ly/l6W0dV can be created. Thirdly, it will be possible to simultaneously look at high resolution while still maintaining the context of the whole chromosome. Finally, this tool will be able to visualize different levels of uncertainty in the data. **Profile** The ideal candidate for this position holds a MSc or PhD degree related to data visualization. He/she should be eager to learn about genomics and variation in the human genome. He/she will collaborate with PhD students and postdocs both at ESAT and the University Hospital in Leuven, as well as with clinical geneticists and international collaborators. The position requires good analytical skills and knowledge of programming languages such as java, ruby or perl. Knowledge of data visualization frameworks such as Processing (http://www.processing.org) and/or Protovis ( http://vis.stanford.edu/protovis/) are a significant plus. We offer a competitive package and a fun, dynamic environment connected to a top-notch consortium of young leading scientists in human genetics and cancer. The University of Leuven is one of Europe’s leading research universities, with English as the working language for research. Leuven is one of Europe’s most beautiful university towns, just outside Brussels, at the heart of Europe. To apply for this position, please send your CV together with a photograph and - if possible - some examples of your work to Prof Jan Aerts ( jan.aerts@esat.kuleuven.be). The deadline for this application is 30th June 2011. Please do not hesitate to forward this message to any interested parties. ================================= Dr Jan Aerts Assistant Professor Faculty of Engineering - ESAT/SCD Kasteelpark Arenberg 10 bus 2446 3001 Leuven-Heverlee (Belgium)