Permanent position on "statistical algorithms and genetical genomics" inside the Applied Mathematics and Computer Science Department of INRA (French National Institute for Agricultural Research) in Toulouse, France.

BACKGROUND

High-throughput technologies in molecular biology allow to probe the cell at the whole-genome scale and to observe molecular networks at different levels (expression of transcripts or proteins, protein-protein or DNA-protein interactions...). It is now clear that the understanding of the underlying mechanisms of molecular networks will necessitate the integration of observations of the cellular system from different point of views in order to built realistic reconstructions and to avoid the effects of noise, which always appears in observations. Genetical genomics is an active area of research (cf. J.Li & M. Burmeister, HMG 2005) which already considers the combination of expression data with polymorphism information inside a population to identify gene regulations. More generally, the integrative reconstruction of molecular networks can be approached through structured probabilistic models (graphical models, bayesian networks...).

J. Li, M. Burmeister, Genetical genomics : combining genetics with gene expression analysis. Human Molecular Genetics 2005, 14.

RESPONSIBILITIES

The candidate will be in charge of developing statistical and mathematical models and algorithms for genetical genomics with application to real data, interacting with biologists.

Mathematical models such as structured probabilistic models allow to describe complex structures which combine heterogeneous observations in a single stochastic framework dealing with noise, biological variability and imperfect modeling. Such models have already been largely used for pedigree or phylogenetical analysis or to try to reconstruct gene regulation networks from expression time-series and genomic sequence data. The development and application of statistical algorithms to infer networks from a variety of data types raises algorithmics issues. Such algorithms should be capable of dealing with complex systems which are only partially captured by the model built.

REQUIREMENTS

The qualified individual will possess a Ph.D. in Statistics, Biostatistics, Bioinformatics, Computer Science or related field.

TERMS: permanent Position

LOCALE: Unité de biometrie intelligence articficelle (INSTITUT NATIONAL DE RECHERCHE AGRONOMIQUE Toulouse France).

The position is opened in the "Statistics and Algorithmics for Biology" team which includes 2 statisticians, 3 computer scientists and different engineers. For contact and more precise information please follow:

http://carlit.toulouse.inra.fr/UBIAT/equipes/saab.html
http://www.inra.fr/drh/cr2008/bdd/cr2/listepardepartement-cr2.php?choix=MIA

COMPENSATION

Depends on the experience. See http://www.inra.fr/les_hommes_et_les_femmes/vous_arrivez_a_l_institut/le_deroulement_de_carriere/le_salaire_et_les_primes (Chargé de recherche, 2e classe).

HOW TO APPLY

See http://www.inra.fr/les_hommes_et_les_femmes/rejoignez_nous/devenir_chercheur_a_l_inra

DEADLINE: 28th february 2008