Wednesday, 19 September 2012

Available: Research position Biological Data Visualization and Visual Analytics


We could still use more applicants for this position, so bumping the open position...

Available: Research position Biological Data Visualization and Visual Analytics


Keywords: biological data visualization; visual analytics; data integration; genomics; postdoc

Are you well-versed in the language of Tufte? Do you believe that visualization plays a key role in understanding data? Do you like to work in close collaboration with domain experts using short iterations? And do you want to use your visualization skills to help us understand what makes a cancer a cancer, and what distinguishes a healthy embryo from one that is not?

We're looking for a motivated data visualization specialist to help biological researchers understand variation within the human genome. Methodologies exist for analyzing this type of data, but are still immature and return very different results depending on what assumptions are made. The type of data can also be used for a huge amount of different research questions, which necessitates developing very exploratory tools to support hypothesis generation.

Profile
The ideal candidate is well-motivated, holds a PhD (or at least MSc) degree in computer science or bioinformatics, and has experience in data visualization (e.g. using tools like D3 [http://d3js.org] or Processing [http://processing.org]). Prior experience working with DNA sequencing data and genome-wide detection of genetic variation would be an advantage but is not crucial. Good communication skills are important for this role.

You will collaborate closely with biologists and contribute to the reporting of the project. You will be able to work semi-independently under the supervision of a senior investigator, mentor PhD students, and contribute to the acquisition of new funding. A three-year commitment is expected. Start date is as soon as possible.

Relevant publications

  • 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)
  • Bartlett C, Cheong S, Hou L, Paquette J, Lum P, Jager G, Battke F, Vehlow C, Heinrich J, Nieselt K, Sakai R, Aerts J & Ray W. An eQTL biological data visualization challenge and approaches from the visualization community. BMC Bioinformatics 13(8):S8 (2012)

Application
For more information and to apply, please contact Jan Aerts (jan.aerts@esat.kuleuven.be, @jandot, +Jan Aerts). If possible, also send screenshots and/or screencasts of previous work.
 
URL: http://www.kuleuven.be/bioinformatics/

Tuesday, 4 September 2012

Postdoc position available: visualization and genomic structural variation discovery

http://www.ftmsglobal.edu.kh/wp-content/uploads/2012/04/Your-Career.jpg

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.

The candidate will collaborate closely with researchers across the consortium and contribute to the reporting of the project. Qualified candidates will be offered the opportunity to work semi-independently under the supervision of a senior investigator, mentor PhD students, and contribute to the acquisition of new funding. A three-year commitment is expected from the candidate. Preferred start date is November/December 2012, so please let us know asap.


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