[sysbio] Postdoc position: Identification of functional modules; Pasteur Institute, Paris, France

Benno Schwikowski benno at pasteur.fr
Sat Apr 12 01:34:46 PDT 2008

*** Postdoctoral position: Approaches for the identification of  
functional modules

The Systems Biology Group at the Pasteur Institute in Paris is looking  
for a motivated computational scientist to join our multidisciplinary  
research group developing new approaches for the identification of  
functional modules in biological subcellular systems. We develop and  
implement algorithms to identify functional modules (i.e., groups of  
functionally related genes and proteins) from high-throughput, large- 
scale data, such as transcriptomic, proteomic, and metabolomic data.  
We develop algorithms and the underlying biological hypotheses in  
close collaboration with computational biologists and experimentalists  
from the BaSysBio consortium (see below).

We are looking for a candidate with a solid background in numerical/ 
optimization algorithms, and programming, and a strong interest in  
molecular and systems biology. Good communication skills and good  
knowledge of English are necessary. Experiences with the computational- 
statistical analysis of large-scale biological data, machine learning,  
and intracellular interactions networks are a plus.

Profile: Ph.D. in a quantitative science, such as applied mathematics,  
statistics, computer science, or physics.

Starting date: June 2008 or later, initially 12 months, extendable to  
2 ½ years.

Please send your CV along with three references until April 27, 2008  
to: Benno Schwikowski, benno at pasteur.fr, http://www.systemsbiology.fr/

*** BaSysBio, a European Integrated Project for Systems Biology

BaSysBio (http://www.basysbio.eu/) is a multidisciplinary project  
involving 16 institutions from 9 countries, in which a systems biology  
approach is used to understand the dynamic transcriptional regulation  
at a global scale in bacteria. In living cells, the regulation of  
transcription is embedded into a hierarchical flow of information from  
genes to phenotype. BaSysBio is generating quantitative data about the  
cellular components at all the levels of the information flow in order  
to understand at the system’s level the highly dynamic regulation of  
genes. High-throughput technologies are developed and adapted to  
facilitate quantitative measurements, in conjunction with the  
development and validation of computational systems biology  
methodologies to enable the quantitative interpretation of the data  
and to unravel the underlying principles of regulatory network  
interactions. Experimental data are generated in the highly tractable  
Gram-positive model bacterium Bacillus subtilis with two specific  
goals: (1) to unravel the global regulatory structure of B. subtilis  
metabolism and understand how transcriptional regulation is integrated  
with the other levels of control; (2) to achieve a quantitative  
understanding of the cellular transcriptional responses under  
conditions mimicking pathogenesis and to apply the acquired knowledge  
and the integrated modelling/experimental strategy developed in the  
model bacterium to understand the regulatory networks controlling  
pathogenesis in the closely related disease-causing bacteria Bacillus  
anthracis and Staphylococcus aureus.

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