[Ieee_vis_open_positions] Postdoctoral scientist - Visual analytic investigation of genomic data

[Jan Aerts]

*Postdoctoral scientist - Visual analytic investigation of genomic data*

Recent technological advancements are changing the face of genetics and
genomics research. Data is now generated at high throughput, and more than
ever a single dataset can be used and reused to address multiple research
questions. As a result, there is an increasing need for tools for
exploration of large amounts of biological data, and generating new
research hypotheses.

Whereas machine learning algorithms and statistics are important in the
field of genetics and genomics, they are primarily aimed at automating
analyses and filtering/prioritizing data. On the other hand, biological
researchers typically use simple plots to investigate their data. This way
of working can however be improved immensely. There are very interesting
opportunities for improving the state of the art in biological data
visualization, including (but far from limited to) integration of different
visualizations, using visualization for cleaning datasets, handling very
large datasets that are difficult to visualize when using naive approaches,
and investigating parameter space of automated algorithms using data
visualization.

To help us in this endeavour, we are looking for a motivated postdoctoral
researcher who is interested in developing novel visual encodings and
underlying infrastructure in the field of biology, mainly focusing around
characterization of structural genomic variation.

The position fits within the SymBioSys consortium of computational
scientists and molecular biologists at the University of Leuven (Belgium),
which investigates how individual genomic variation leads to disease
through cascading effects across biological networks. This consortium has
primary access to different DNA sequencing technologies (454, Illumina
HiSeq, PacBio) and is at the forefront of research in single-cell genomics,
constitutional disorders and cancer.

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 either in bioinformatics/genomics or
in a field relevant for (biological) data visualization. Programming and
data analysis experience is essential. 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. Prior
experience working with sequencing data, i.c. alignment of next-generation
data, as well as genome-wide detection of genetic variation would be an
advantage but are not essential. 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 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)
   - Sifrim A, Van Houdt JKJ, Tranchevent L-C, Nowakowska B, Sakai R,
   Pavlopoulos GA, Devriendt K, Vermeesch JR, Moreau Y & Aerts J.
   Interpretation of single nucleotide variation in human disease: a
   Swiss-knife approach to annotation and analysis. Genome Medicine 4(9):73
   (2012)
   - Bartlett C, Cheong SY, Hou L, Paquette J, Lum PY, Jaeger G, Battke F,
   Vehlow C, Heinrich J, Nieselt K, Sakai R, Aerts J & Ray WC. An eQTL
   biological data visualization challenge and approaches from the
   visualization community. BMC Bioinformatics 13(Suppl 8):S8 (2012)

*How to apply*

Please send in PDF:

   1. a CV including education, research experience, and bibliography
   2. a one-page research statement
   3. two references (with phone and email)
   4. if available: one or more figures and/or screencasts of previous
   visualization work

to Prof Jan Aerts (jan.aerts at esat.kuleuven.be), cc Prof Yves Moreau (
yves.moreau at esat.kuleuven.be) and Ms Ida Tassens (
ida.tassens at esat.kuleuven.be). Pre-application inquiries can be sent to
jan.aerts at esat.kuleuven.be.

URL: http://www.kuleuven.be/bioinformatics/

================================
Dr Jan Aerts
Assistant Professor
Faculty of Engineering - ESAT/SCD
University of Leuven
Kasteelpark Arenberg 10 bus 2446
3001 Leuven-Heverlee
Tel: +32 16 321053
Fax: +32 16 321970
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