Job Code : RCI-GT-33985

Job Title: Computational Scientist

Location: Mississauga, Ontario, Canada

Duration: 12 Month extension possible based on needs and performance

Minimum Salary: $58.00 Per Hourly

Maximum Salary: $63.00 Per Hourly

This is a hybrid role.

The position

• The Oncology team in the Computational Biology and Translation Pillar of gRED Computational Sciences (gCS) is seeking a talented and highly motivated Computational Scientist (Contract) with a strong analytical background in computational biology and cancer, particularly focusing on Breast Cancer.
• The ideal candidate will have a demonstrated ability to apply both standard and advanced computational methods (e.g., statistical modeling, machine learning), and a passion for generating insights from preclinical and clinical datasets.

Position Details

Responsibilities

• Work under the supervision of a group leader in Computational Biology and Translation Oncology to analyze large-scale bulk RNA, ATAC and WES datasets as well as single-cell datasets to address scientific hypotheses and deliver novel insights for drug development.
• Develop analytical approaches to integrate and interpret these data, delivering insights into disease biology and drug mechanisms of action to propel our pipeline and research goals.
• Present analysis results and research findings to stakeholders and address follow-up questions in a semi-independent manner.
• Document code, analysis processes, and findings, including standardization of analytical workflows.

Requirements

• Ph.D. in Computational Biology, Systems Biology, or Bioinformatics with additional experience as an individual contributor (postdoc is a plus).
• Track records of publications in Computational Biology or Cancer Biology.

Extensive experience (6+ years) in large-scale bulk data analysis (RNA, WES), including gold-standard methods and novel, advanced analytical techniques such as:

• Multivariate statistical analyses
• Analysis of drug response and perturbational data
• Multimodal data integration methods
• Predictive/Prognostic analyses
• Expertise in the following areas: cancer biology, omics data, multimodal data, drug response data, and breast cancer.
• Proficiency in R, Python, and shell scripting.
• Experience working with Git and high-performance computing.
• High self-motivation and commitment to delivering high-quality results.
• Ability to produce high-quality analysis results with minimal supervision, including meeting key deadlines and making sensible independent decisions.
• Excellent communication skills and experience working as part of a team.
• Curiosity and desire to learn more about Computational Biology and Breast Cancer.