Job Description

Computational Biologist

Location: Remote, must be able to work PST

Duration: contract through end of 2025 with probability of extensions

ASAP Start

Position Details

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 data from Breast Cancer patients. The successful candidate will have a proven track record

in multi-omics analysis and the application of both standard and advanced computational

methods, such as statistical modeling, machine learning, and bioinformatics pipelines, for

hypothesis testing and novel insight generation on clinical data.

Responsibilities

• Collaborate with scientists in Computational Oncology to analyze large-scale bulk RNA and WES clinical datasets to address scientific hypotheses and deliver novel insights.
• Develop analytical approaches to integrate and interpret these data, delivering insights into disease biology and mechanisms of action to propel our pipeline and clinical research goals.
• Document code, analysis processes, and findings, including standardization of analytical workflows.

Requirements

• 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
• Multimodal data integration methods
• Predictive/Prognostic analyses
• Expertise in any of the following areas: cancer biology, clinical omics data, real-world data, breast cancer.
• PhD in Computational Biology, Bioinformatics, or a related field.
• 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.

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