Computational Biologist

Medasource; South San Francisco (CA); Remote; USD 80,000 - 130,000; Full time

Job summary

An innovative firm in the biotechnology sector is on the lookout for a skilled Computational Scientist to join their Oncology team. This exciting contract role focuses on analyzing complex datasets from Breast Cancer patients, utilizing advanced computational methods to generate novel insights. The ideal candidate will possess a strong analytical background and extensive experience in multi-omics analysis, statistical modeling, and bioinformatics. With a commitment to high-quality results and a collaborative spirit, you'll be instrumental in driving clinical research goals forward. If you're passionate about computational biology and eager to make a meaningful impact, this opportunity is perfect for you.

Qualifications

• 6+ years of experience in large-scale bulk data analysis, including RNA and WES.
• Expertise in cancer biology and clinical omics data.

Responsibilities

• Collaborate with scientists to analyze large-scale clinical datasets.
• Develop analytical approaches to interpret data and deliver insights.

Skills

Data Analysis

Statistical Modeling

Machine Learning

Bioinformatics

Communication Skills

Self-Motivation

Education

PhD in Computational Biology

PhD in Bioinformatics

Tools

R

Python

Git

High-Performance Computing

Shell Scripting

Job description

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Professional Life Sciences Recruiter at Medasource

Computational Biologist

Location: Remote, must be able to work PST

Duration: contract through end of 2025 with probability of extensions

ASAP Start

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
• 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.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Analyst, Research, and Other

Industries

Pharmaceutical Manufacturing and Biotechnology Research