Bioinformatics Scientist

Job Title: Digital Trainer: Bioinformatics Scientist
Job Location: Mississauga, ON (L5N 5M8)
Job Duration: 6 Months (possibility of extension)

Job description:
We are a team of highly experienced and collaborative bioinformaticians and we are seeking a qualified intern to help us leverage state-of-the-art AI for healthcare. Your work will involve research and development of AI-based bioinformatics applications for multiple kinds of biological data, particularly next-generation sequencing (NGS). Working on the crossroads of state of the art in AI and bioinformatics will equip you with the skills and experience of applying AI in improving patients’ lives.
We are seeking a highly motivated and analytical Bioinformatics contractor to join our computational biology team. In this full-time role, you will be at the forefront of liquid biopsy research. Your work will directly contribute to the computational development of our next-gen NGS assays, helping push the boundaries of personalized medicine.
 
Key Responsibilities:

• Pipeline Execution & Optimization: Assist in developing, testing, and optimizing bioinformatics pipelines for the identification and quantification of genetic mutations from cfDNA NGS datasets.
• Data Visualization: Create clear, clarifying visualizations of genomic data, coverage maps, and biomarker characteristics, to present findings to the cross-functional R&D team.
• Data Analysis: Analyze genetic mutations identified in cfDNA; propose and explore Client biomarkers; build reproducible machine learning models to quantitatively assess and validate biomarkers.
• Collaboration: Work closely with senior bioinformaticians to troubleshoot analysis strategies and correlate computational findings with clinical data.

 
Minimum Qualifications:

• Education: Bachelor’s or Master’s degree or higher in Bioinformatics, Computational Biology, Computer Science, Biostatistics, or a closely related field.
• Programming Skills: Strong proficiency in Python and Bash/Client scripting within a Linux/Unix environment and familiarity with good engineering practices including proper use of generative AI, version control, and documentation.
• High-performance computing: Proficient in scaling bioinformatics pipelines across HPC clusters using Slurm or equivalent to accelerate NGS data processing.
• Genomic Fundamentals: Solid understanding of Next-Generation Sequencing (NGS) technologies, sequence alignment, and structural variant detection.
• Machine learning: Familiarity with common machine learning concepts, models, metrics and frameworks (scikit-learn, pandas etc).

 
Preferred Qualifications:

• Familiarity with workflow management systems (Nextflow, Snakemake) and containerization (Docker, Singularity or equivalent).
• Prior exposure to liquid biopsy data (cfDNA/ctDNA) or cancer genomics.

Strong track record of data analysis and publication in relevant fields is a plus.