new
Institution/Company:

Simon Fraser University

Location:

Burnaby

, British Columbia

 Canada

Job Type:

Research Associate

Degree Level Required:

Bachelor's, Masters

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Description Responsibilities Qualifications Additional Information
Description:

Overview and duties:

The Lee Laboratory in the Department of Molecular Biology and Biochemistry at Simon Fraser University (SFU) is seeking a Bioinformatics Data Analyst with experience in high-throughput sequencing data analysis (https://sfu-lee-lab.github.io/Lee_Lab_Webpage/).
The primary responsibility of the successful candidate will be to process and analyze next-generation sequencing data, particularly in microbial genomics, host transcriptomics, and integrative multi-omics analyses. The candidate will also support data analysis for trainees in the group and prepare technical documentation for grant reports and other reporting needs. The candidate will join an interdisciplinary team of approximately 10 people, working closely with molecular biologists and computational scientists. The primary work location is SFU’s Burnaby campus in Greater Vancouver. The campus sits within the Burnaby Mountain Conservation Area, about 15 km from the City of Vancouver.

Responsibilities:

– Process and analyze microbial genomics, host RNA-seq, and multi-omics data
– Collaborate with wet-lab scientists to design experiments, analyze data, and interpret results
– Design and implement analysis workflows using workflow managers such as Nextflow or Snakemake
– Package pipelines using container technologies and deploy them on computing clusters
– Support trainees with data analysis and provide training in bioinformatics methods
– Document code, pipelines, and analyses, and contribute to manuscripts, grant reports, and other reporting
– Participate in scientific discussions and present results at lab meetings and conferences

Qualifications:

– BSc or MSc in computer science, bioinformatics, computational biology, or a related field, or equivalent experience
– Demonstrated experience analyzing genomic and high-throughput sequencing data
– Strong analytical skills and a solid foundation in statistics
– Proficiency in R and Python, and in shell scripting to automate tasks in a Unix/Linux environment
– Demonstrated ability in R or other similar statistical programming languages
– Excellent oral and written communication skills, including the ability to organize and communicate scientific data and document code clearly
– Strong attention to detail, self-motivation, and the ability to manage multiple projects in a multidisciplinary environment
– Demonstrated ability to work effectively in a team

Additional Information:

Strong Assets:

– Experience with microbial genomics data, including assembly, annotation, and comparative genomics
– Experience with host transcriptomic analyses, such as differential expression and pathway or network analysis
– Experience with machine learning models (e.g., elastic net, LASSO, random forest) and feature selection for biomarker discovery
– Experience designing and building robust computational pipelines in a Unix-like environment
– Familiarity with sequencing platforms such as Illumina and Oxford Nanopore and their associated analysis tools
– Familiarity with high-performance computing (e.g., Digital Research Alliance of Canada clusters) and containerization (e.g., Docker)
– Familiarity with version control and reproducible research tools such as Git and GitHub

To Apply:

– Please send your cover letter, CV, and the names and contact information of two referees, combined into a single PDF, to (lee.lab.sfu.hiring@gmail.com) with the subject line “Bioinformatics_Analyst”. We thank all applicants; only those selected for an interview will be contacted.

Keywords:

Bioinformatics

Machine Learning

Genome Assembly

Transcriptomics

NGS

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