Bioinformatics Analyst

1 month ago


Saskatoon, Saskatchewan, Canada University of Saskatchewan Full time
Job Title: Bioinformatics Analyst

Join our team at the University of Saskatchewan as a Bioinformatics Analyst in the Cancer Research Unit. We are seeking a highly skilled and motivated individual to provide bioinformatics expertise and support for health science researchers.

Job Summary:

The successful candidate will have experience analyzing publicly available and newly generated genomics and transcriptomics data in a Linux/UNIX environment. They will assist researchers in analyzing and interpreting results in an oncological context.

Key Responsibilities:
  • Process and analyze researcher-generated sequencing data, including data quality assessment and generating results using custom and established pipelines and workflows.
  • Analyze large public databases, particularly those containing 'omics and clinical data, such as cBioportal, TCGA, and gnomAD.
  • Research, implement, and validate bioinformatic tools for specific project analyses.
  • Troubleshoot software and scripts.
  • Streamline and maintain NGS data analysis pipelines and manage storage of datasets and results.
  • Organize results into clear presentations, figures, or summaries.
Requirements:
  • Bachelor's degree in bioinformatics, computational biology, genomics, or a related field with 2 years of experience.
  • Previous experience performing processing and analyzing genomic and transcriptomic data is required.
  • Strong programming skills using multiple languages, including Python, Bash, and R.
  • Proficient in utilizing and programming within a High-Performance Computing (HPC) environment.
  • Excellent communication skills and ability to communicate results effectively to researchers.
Preferred Qualifications:
  • Master's or PhD degree in bioinformatics, computational biology, genomics, or a related field.
  • Experience with Chip-Seq, ATAC-Seq, scRNA-Seq, and other high-throughput sequencing technologies.
  • Experience integrating data from major public sources to inform subsequent analyses.
  • Experience using software tools and resources, such as Ingenuity Pathway Analysis (IPA), Bioconductor, and Conda.


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