Job Title: Computational Scientist - Oncology

Location: Mississauga, ON- Hybrid

Duration: 12 Months+

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

This position can be remote (US or Canada) during normal Pacific timezone business hours.

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 Client 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 Client, advanced analytical techniques such as:

o Multivariate statistical analyses

o Analysis of drug response and perturbational data

o Multimodal data integration methods

o 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 Client 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.