Mots-Clés

multi-omics epigenomics gene co-expression gene regulatory networks neuropsychiatric disorders

Description

The Integrative Genomics in Neurodevelopment group, is seeking a highly motivated research engineer. The group is part of the NeuroDiderot INSERM research unit, located in the Robert Debré Hospital. The "Integrative Genomics in Neurodevelopment group" carry out advanced systems biology approaches, at the intersection of data science, genomics, and drug discovery, to identify molecular drivers and new therapeutical options for neuropsychiatric disorders. 

The successful candidate will be involved in the FAME project (Improving Family Members’ Experience in the Intensive Care Units) and in related research projects which aim at characterizing the molecular landscape (genomic, transcriptomic and epigenomic) of the development of neuropsychiatric disorders. Post-traumatic disorder (PTSD) affects one third of family members of Intensive Care Unit patients. In the FAME project, blood samples and follow-up data are collected for 350 family members in order to develop personalized predictive models of the occurence of PTSD. The engineer will be in charge of the development, the organisation and the application of innovative computational pipelines to analyze multiple types of (epi)genomic data.

Tasks

• Support the data generation and management of data in the FAME project and in other projects
• Test, improve and deploy to production in-house pipelines for multi-omic data integration, gene co-expression, regulatory network analyses, candidate biomarker identification, candidate drug prioritisation
• Perform end-to-end data analysis (QC, processing, normalization, visualization) of various omic data sets
• Organize the analysis and storage of large in-house (FAME project, related projects) and open-source data sets
• Maintain and organize analysis pipelines and packages developed in the group

Experience / Skills

• Training in bioinformatics, statistics, or data science with knowledge and interest in biology
• Experience working in a Unix environment and statistical analysis using R and Python
• Experience with (epi)genomic/transcriptome data analysis would be a significant asset
• Conceptual background in neurosciences would be an asset