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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.
Profile
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.
Relevant
publications
- 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)
Application
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
(jan.aerts@esat.kuleuven.be), cc Dr Yves Moreau (yves.moreau@esat.kuleuven.be)
and Ms Ida Tassens (ida.tassens@esat.kuleuven.be).
URL: http://www.kuleuven.be/bioinformatics/http://www.kuleuven.be/bioinformatics/
To apply : http://phd.kuleuven.be/set/postdoc/voorstellen_departement?departement=50000516http://phd.kuleuven.be/set/postdoc/voorstellen_departement?departement=50000516
