[SocBiN] KU Leuven - Postdoctoral computer scientist – Kernel methods and network analysis for data fusion in chemobioinformatics

[mimi deprez]

Dear 
On behalf of prof Moreau would it be possible to send out our jobopening to all your list members?

please find the details of the position below :


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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

Keywords: machine learning, bioinformatics, chemoinformatics

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. Methodological research results will be published as academic research articles.

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.

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 Ms. Mimi Deprez (mimi.deprez 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 Yves.Moreau at esat.kuleuven.be.

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









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Mimi Deprez
Project Coordinator
KU Leuven - University of Leuven 
Dept. Elektrotechniek-ESAT-STADIUS
(STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics)
iMinds Department Medical Information Technologies 


t:+ 32 (0) 16 32 85 55 m: + 32 476 72 68 59
Kasteelpark Arenberg 10, bus 2446
B-3001 Leuven

http://www.esat.kuleuven.be
http://www.kuleuven.be/iMinds/

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