Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : Loria (Laboratoire Lorrain de Recherche en Informatique et ses Applications), UMR7503 (CNRS-University of Lorraine and Inria)
Durée : 12 months (renewable)
Contact : marie-dominique.devignes@loria.fr
Date limite de publication : 2018/02/28
Contexte :
The Centre Hospitalier Regional Universitaire (CHRU) of Nancy supports collaborations with research organisms through Interface Contracts, during which permanent scientists come and work with clinicians to share their skills and contribute to research efforts with new analyses methods. These Interface Contracts benefit from associated post-doctoral fellowships.
This post-doc offer is associated with MD Devignes’s interface contract. MD Devignes is a CNRS scientist at the LORIA, member of the Capsid team. The general objective of her contract is to apply data integration and data mining methods, including domain knowledge, to biomedical data in order to expand the exploitation and valorisation of these data.
The topic of this post-doc offer is part of a hospitalo-universitary research project about Heart Failure in which a workpackage (coordinated by MD Devignes) is dedicated to complex networks analysis, in order to improve the classification and interpretation of various types of heart failure.
Moreover, this position is related to the development at the Loria of a shared ressource platform for « data science for healthcare », displaying high-performance computing facilities, and that benefits from the service of an engineer for software and database deployment.
Sujet :
GraphScore – Definition and evaluation of graph scores for the identification of biomarkers in complex interaction networks.
The post-doctoral project concerns the analysis of complex interaction networks. The main ressource at our disposal is a huge graph database representing various types of interactions between various groups of elements : proteins, diseases, drugs, etc. One objective of the project is to exploit this ressource to identify new biomarkers of certain heart-failure mechanisms.
The queries on the main graph database most often return subgraphs such as the shortest paths between proteins or drugs of interest and a disease. In order to avoid manual inspection of all these subgraphs, some graph scoring should be defined in order to rank the subgraphs according to given points of view and to analyze first the most relevant ones. The graph scoring method should combine graph topological properties and any other properties attached as attributes to the graph nodes and edges, these latter properties being expressed in controlled vocabularies or ontologies.
Several graph scoring methods will be defined with the help of bioinformaticians, biostatisticiens et FIGHT-HF clinicians. The post-doctoral scientist will develop score calculation, and design and run evaluation studies, based for instance on already known biomarkers.
Profil du candidat :
Computer scientist, trained in graph/network analyses, seeking a post-doctoral fellowship, preferably with some experience after the PhD thesis.
An experience in working in an inter-disciplinary environment related to health or biology will be appreciated.
Formation et compétences requises :
PhD thesis in Computer Science or Applied Mathematics dealing with complex graph analysis or mining.
Computer Science skills: relational database (ex : MySQL), graph-oriented databases (ex : Neo4J), knowledge bases, safety of information systems, programming languages (bash, python, R, php, java, others…), knowledge in statistics and in supervised or unsupervised classification/machine learning.
Some knowledge about biological databases, information retrieval and/or high-performance computing.
Adresse d’emploi :
LORIA (UMR7503), Campus de la Faculté des Sciences et des Technologies, BP239, 54500 Vandoeuvre les Nancy, France
Document attaché : POSTDOCjoboffer_GraphScore_LORIANancy.pdf