Bioinformatician with experience in single-cell approaches or RNA seq

The McGill Group for Suicide Studies is a multidisciplinary team of researchers using complementary approaches to understand what makes people at risk for depression and suicide. We are looking to hire a bioinformatician with experience in novel techniques for analyzing multi-omic data generated from individual cells. This person will be asked to work alongside students on projects dealing with the functional genomics of major depressive disorder and suicide, but in many instances will be expected to lead the computational strategies.

Additionally, we study various aspects of the function genome by generating whole genome/transcriptome datasets which include but are not limited to; RNA-seq DNA and RNA methylation, using conversion-based sequencing (bisulfite or APOBEC) or ChIP-seq approaches. As part of their work, the bioinformatician will be expected to process next-generation sequencing (NGS) data, from raw reads to final output, using the appropriate bioinformatic tools and pipelines on high-performance computer clusters.

The primary task will be to perform in-depth primary and tertiary analyses on single-cell omic datasets. This will require the implementation of novel tools, the standardization of pipelines for cell clustering and annotation, and downstream differential state analysis.

The application will be expected to attend single-cell bioinformatic meetings hosted by the Single-cell academy, as well as, weekly meetings within the MGSS.

Analyzing NGS methylation datasets from start to finish, carrying quality control checks on the sequenced libraries, identifying and removing sequencing biases, aligning reads to the genome, extracting relevant methylation metrics (signal, percentage, position, context, motif, etc.), and conducting downstream statistical analyses.

Furthermore, they will need to synthesize the results and clearly communicate and transfer the data to other lab members. Analyses are often conducted in the context of students’ projects; it is of the utmost importance that students understand what has been done to the data and what to be mindful of when continuing the work.

The bioinformatician is expected to manage the data they generate and its backup. Keeping a detailed log of how analyses were carried out in order to facilitate transparency and reproducibility of the results. They are also expected to manage their own time according to the various deadlines of the projects they are working on.

• Previous experience in single-cell data analyses
• A good understanding of biochemistry is necessary.
• Fluency in either French or English, as well as being at least conversational in the other is required.
• Good communication and people skills.
• Good time management and organizational skills.
• Creative problem-solving.

General computer abilities:
• Experienced user of UNIX and working on Linux environments through the command line. (At least 5 years experience)
• Proficiency in Bash and at least one of the following scripting languages (Perl, Python, Ruby).
• Knowledge of R and Bioconductor is preferred. Knowledge of other programming languages is a plus
• Good understanding of statistics is preferred.
• Experience working with large datasets is required
• Experience with the Compute Canada high-performance clusters is an asset.

Bioinformatic abilities:
• Experience with 10x pipelines (CellRanger, SpaceRanger, Seurat etc)
• Experience with analyzing NGS data is required
• Familiarity with sequencing reads cleaning and trimming tools.
• Experience with sequence aligners is required (specifically bowtie2 and STAR).
• Experience with bismark is an advantage.
• Experience working with ChIP-seq data would be ideal
• Relevant tools and software: MACS2, ExomePeaks, HOMER
• Familiarity with the large -OMICs databases (ei. NCBI, ENSEMBL, UCSC)
• Knowledge of machine learning is welcome but not necessary