SymBioSys is a consortium of computational scientists and molecular biologists at the University of Leuven, Belgium focusing on how individual genomic variation leads to disease through cascading effects across biological networks (in specific types of constitutional disorders and cancers). We develop innovative computational strategies for next-generation sequencing and biological network analysis, with demonstrated impact on actual biological breakthroughs.
The candidate will be a key player in the SymBioSys workpackage that focuses on genomic variation detection based on next-generation sequencing data (454, Illumina, PacBio) using a visual analytics approach (i.e. combining machine learning with interactive data visualization). This includes applying and improving existing algorithms and tools for the detection of structural genomic variation (insertions, deletions, inversions and translocations), as well as developing interactive data visualizations in order to investigate parameter space of these algorithms. These methods will be applied to specific genetic disorders in day-to-day collaboration with the human geneticists within the consortium.
We offer a competitive package and a fun, dynamic environment with a top-notch consortium of young leading scientists in bioinformatics, human genetics and cancer. Our consortium offers a rare level of interdisciplinarity, from machine learning algorithms and data visualization to fundamental advances in molecular biology, to direct access to the clinic. The University of Leuven is one of Europe’s leading research universities, with English as the working language for research. Leuven lies just east of Brussels, at the heart of Europe.
The ideal candidate holds a PhD degree in bioinformatics/genomics and has good analytical, algorithmic and mathematical skills. Programming and data analysis experience is essential. Prior experience working with sequencing data, i.c. alignment of next-generation data, as well as genome-wide detection of genetic variation would be a distinct advantage. Experience in data visualization - e.g. using tools like D3 (http://d3js.org) or Processing (http://processing.org) - would also be considered a big plus. Good communication skills are important for this role.
- Conrad D, Pinto D, Redon R, Feuk L, Gokumen O, Zhang Y, Aerts J, Andrews D, Barnes C, Campbell P et al. Origins and functional impact of copy number variation in the human genome. Nature 464:704-712 (2010)
- Medvedev P, Stanciu M & Brudno M. Computational methods for discovering structural variation with next-generation sequencing. Nat Methods 6(11):S13-S20 (2009)
- Nielsen CB, Cantor M, Dubchak I, Gordon D & Ting W. Visualizing genomes: techniques and challenges. Nat Methods 7:S5-S15 (2010)
Please send in PDF: (1) a CV including education (with Grade Point Average, class rank, honors, etc.), research experience, and bibliography, (2) a one-page research statement, and (3) two references (with phone and email) to Dr Jan Aerts (email@example.com), cc Dr Yves Moreau (firstname.lastname@example.org) and Ms Ida Tassens (email@example.com).
To apply : http://phd.kuleuven.be/set/postdoc/voorstellen_departement?departement=50000516http://phd.kuleuven.be/set/postdoc/voorstellen_departement?departement=50000516