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Postdoctoral computer scientist – Kernel methods and
network analysis for data fusion in chemobioinformatics
University of Leuven
ESAT-STADIUS
SymBioSys Center for Computational Systems Biology
In the framework of a collaboration with Janssen
Pharmaceuticals, we are looking for a talented postdoctoral researcher
to develop kernel methods that link drug targets, disease phenotypes,
and pharmaceutical compounds. Leveraging large-scale public and
in-house data sets, you will develop kernel methods and/or
network-based methods to predict potential links between targets,
diseases, or candidate drugs. This research builds upon the expertise of
Janssen Pharma and previous work of our team on genomic data fusion.
The research will be also carried out with a team of the University of
Linz, Austria (Prof. Sepp Hochreiter) specialized in kernel learning
and chemoinformatics.
Genomic data fusion (Moreau and Tranchevent, 2012;
Aerts et al., 2006) offers a range of approaches to tackle
the challenge described above. Among such methods, the University of
Leuven has pioneered the use of kernel methods to integrate heterogeneous
omics data (De Bie et al., 2007; Yu et al., 2009). The key
advantage of kernel methods for mining heterogeneous data is that when
multiple data sets are available, they all lead to kernel similarity
matrices independently of the original type of data. Those kernels
can then be efficiently integrated using Multiple Kernel Learning (De Bie
et al., 2007; Yu et al., 2009). Similarly, our team has developed
network analysis methods using kernel diffusion to identify potential
targets of a drug. The goal of the project is to refine and generalize
these methods to the complex and large-scale data sets available at a
major pharmaceutical company.
The STADIUS Center for Dynamical Systems, Signal
Processing, and Data Analytics at KU Leuven is an academic research
center, with a research focus on mathematical engineering, where
mathematical tools from numerical linear and multi-linear algebra,
statistics and optimization are used for applications of dynamical systems
and control, signal processing, data modeling and analytics. The
project is embedded within the SymBioSys Center for
Computational Systems Biology, a universitywide center aiming at
linking genomic variation to disease, and within the Exascience Life Lab,
a major collaboration on scaling up genomic data analysis methods at
exaflop scale. 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 computer
science or computational biology. Experience with machine learning, in
particular kernel methods, is a core asset. Ability to develop powerful
machine learning algorithms and scale them up to large data sets
is essential. Capacity to plan and deliver on time, as well as
strong communication skills, are important to manage a successful
collaboration with our pharmaceutical and academic partners. A two-year commitment
is expected from the candidate. Preferred start date is July
2014.
RELEVANT PUBLICATIONS
Moreau Y, Tranchevent LC. Computational tools for
prioritizing candidate genes: boosting disease gene discovery. Nat
Rev Genet. 2012 Jul 3;13(8):523-36.
Yu S, Falck T, Daemen A, Tranchevent LC, Suykens JA, De
Moor B, Moreau Y. L2-norm multiple kernel learning and its application to
biomedical data fusion. BMC Bioinformatics. 2010 Jun 8;11:309.
De Bie T, Tranchevent LC, van Oeffelen LM, Moreau Y.
Kernel-based data fusion for gene prioritization. Bioinformatics. 2007 Jul
1;23(13):i125-32.
Aerts S, Lambrechts D, Maity S, Van Loo P, Coessens B, De
Smet F, Tranchevent LC, De Moor B, Marynen P, Hassan B, Carmeliet P,
Moreau Y. Gene prioritization through genomic data fusion. Nat Biotechnol.
2006 May;24(5):537-44.
Laenen G, Thorrez L, Börnigen D, Moreau Y. Finding the
targets of a drug by integration of gene expression data with
a protein interaction network. Mol Biosyst. 2013 Jul;9(7):1676-85.
HOW TO APPLY
(Publication date of the vacancy: May 15, 2014)
Please send in PDF at your earliest convenience:
1. CV including education, research
experience, and bibliography
2. Three references (with phone and email)
3. A statement of purpose describing why you are qualified
for the position and what your contribution could be
to Mrs. Mimi Deprez (mimi.deprez@esat.kuleuven.be), cc Prof. Yves Moreau (yves.moreau@esat.kuleuven.be), and Ms. Ida Tassens (ida.tassens@esat.kuleuven.be).
Pre-application inquiries can be sent to Yves.Moreau@esat.kuleuven.be.
URL: http://www.kuleuven.be/bioinformatics
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