SnoRNAs are best known for their role in ribosomal RNA (rRNA) modification but the majority of snoRNAs have no known function or have other roles in gene expression regulation. We are using a multidisciplinary approach to uncover the function of snoRNAs by building networks of RNA and protein interactomes. Networks are built through cycles of computational prediction and experimental validation. The successful applicant will work with a team of experimental and computational biologists to integrate RNA-RNA and RNA-protein interactions, protein abundance, snoRNA abundance and mRNA abundance datasets to discover functional relationships and link it to cellular phenotypes.
Applicants should have a recent (<3 years) Ph.D. in quantitative sciences with proficiency in bioinformatics and transcriptomics. Candidates with a background in network biology, machine learning, and RNA biology will be preferentially considered. A good ability to use written and spoken English is required, French is optional. Only candidates with relevant publication record will be considered.
Email CV and motivation letter