Research Associate- Production Bioinformatics

Responsibilities:

Perform initial stage analysis on next-generation sequencing data transforming data from sequence to information meaningful for biologists; Continuous interaction with the production development team to ensure that the NG sequencing software pipeline is consistently, reliably, efficiently and correctly processing data; Ensure that data is managed efficiently, securely, and without loss or corruption through its lifecycle; Provide bioinformatics support and training to end-users (research laboratory staff, remotely located collaborative users); Responsible for researching, planning, implementing, and testing bioinformatics software tools that meet the analysis needs for specific collaborative projects Development and support of tools and protocols for data deposition to external repositories that meet release cycles and publication requirements. Work with 3rd party software vendors to characterize and resolve problems with production software systems; Responsible for documenting and communicating pipeline processes and building the team knowledge base.

Qualifications:

Bachelor’s or master’s degree in related discipline, with demonstrated experience in the skill set; Must have advanced skills in Unix shell programming environment; Proficiency with some Unix based scripting language (Perl, Python etc.) required; Experience with statistical and graphical software packages (R) and associated bioinformatics libraries is essential. IT knowledge (HPC and data storage) is desirable; Must have excellent communications (in one of NB’s official language – French/English) and interpersonal skills; Experience supporting a high availability production software environment; Experience providing end-user software support, diagnosing and resolving end-user issues; Experience working in a multidisciplinary team environment; Experience with next generation sequencing analysis is highly desirable. If the candidate has experience with the Life Technologies Ion Torrent and Ion Proton, Oxford Nanopore MinIon sequencing platforms is an extra; Experience in the development of Machine Learning applications (among others Deep Neural Networks) in the direction of identifying patterns within Next Generation Sequencing Data from RNA and DNA would be an asset.