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Contract Cancer Bioinformatics Jobs in California

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Contract Cancer Bioinformatics information

What is a contract cancer bioinformatics specialist?

Contract Cancer Bioinformaticians are professionals who specialize in analyzing biological data related to cancer, typically working on a contractual or project basis rather than as permanent staff. They use computational tools and statistical techniques to interpret large datasets, such as genomic or proteomic data, to support cancer research and clinical decision-making. These specialists collaborate with biologists, clinicians, and other researchers to uncover insights into cancer development, progression, and treatment. Their roles may involve developing pipelines, conducting data analysis, and helping design experiments to advance cancer understanding and therapies.

What are the key skills and qualifications needed to thrive as a contract cancer bioinformatics specialist?

To excel as a Contract Cancer Bioinformatics Specialist, you need a strong background in bioinformatics, molecular biology, statistics, and experience analyzing large-scale genomic data, often supported by an advanced degree in a relevant field. Proficiency in programming languages like Python or R, familiarity with next-generation sequencing (NGS) analysis tools, and experience using databases such as TCGA or cBioPortal are typically required. Exceptional problem-solving, attention to detail, and effective communication skills are crucial for collaborating with multidisciplinary research teams and translating complex data into actionable insights. These competencies are vital for driving impactful cancer research and ensuring accurate, reproducible data analysis in a fast-paced, project-based environment.

What are some common challenges faced by contract cancer bioinformatics specialists, and how can they prepare for them?

Contract cancer bioinformaticians often encounter challenges such as rapidly adapting to new datasets, integrating with diverse research teams, and managing tight project timelines. Since contracts may vary in scope and duration, it's important to quickly understand project objectives and existing workflows. Building strong communication skills and staying current with the latest bioinformatics tools and cancer research trends can help you excel in this role. Establishing clear expectations with clients and maintaining organized documentation also contribute to successful contract engagements.

What are the most commonly searched types of Cancer Bioinformatics jobs in California?

The most popular types of Cancer Bioinformatics jobs in California are:

What are popular job titles related to Contract Cancer Bioinformatics jobs in California?

For Contract Cancer Bioinformatics jobs in California, the most frequently searched job titles are:

What job categories do people searching Contract Cancer Bioinformatics jobs in California look for?

The top searched job categories for Contract Cancer Bioinformatics jobs in California are:

What cities in California are hiring for Contract Cancer Bioinformatics jobs?

Cities in California with the most Contract Cancer Bioinformatics job openings:

Contract Cancer Bioinformatics jobs near you

Computational Clinical Scientist II, Clinical Bioinformatics

Revolution Medicines

Redwood City, CA • Hybrid

Full-time

Posted 12 days ago

Job description

The Opportunity:

In this role, you will work within our Translational Medicine group analyzing and interpreting molecular and clinical data. Analysis will focus on using genomic, protein and other targeted assays to identify and validate predictive biomarkers. The computational clinical scientist will work on various projects in different phases of drug development and contribute to the cross-functional team which includes other bioinformaticians, program leads, medical monitors, biostatisticians other pre-clinical scientists.

  • Integrate multiple data sources including circulating tumor DNA, patient enrollment data, molecular profiling (RNA/DNA sequencing outputs), multiplex immunohistochemistry to identify and validate new biomarkers for candidate drugs.

  • Work with internal groups, contract research organizations and collaborators to deliver validated biomarker data and analysis.

  • Support the development of biomarker related aspects of the trial design where bioinformatic analysis is required, including study protocols, lab manuals, clinical study reports, and other regulatory documents.

  • Work with biomarker scientists to support analysis of biomarker readouts (summary statistics, and visualization of efficacy in molecular subgroups).

  • Collaborate with preclinical bioinformaticians to design, analyze and interpret experiments to validate biomarkers, understand compound mechanism of action, and identify biomarkers for patient selection and target engagement.

Required Skills, Experience and Education:

  • M.S. or Ph.D. in bioinformatics, biology, data science or a related field with emphasis on biological data analysis.

  • 2+ years of pharmaceutical or biotech experience in bioinformatics focused on oncology, immunology, or related field.

  • Proficiency and experience programming using R and/or Python.

  • Proficiency in statistical models and analysis of clinical data. Some ML experience a strong plus.

  • Proficiency in visualizations and faceting of molecular data necessary (oncoplots, heatmaps, PCA, etc.).

  • Experience with efficacy, baseline demographic, and other outcome data generated in a clinical trial.

  • Experience with statistical methods i.e. survival analysis, and causal inference.

  • Expertise in bioinformatic analysis of cancer signaling pathways and driver mutations.

  • Experience in tools to analyze cancer genomics data types (RNA, WES, ctDNA, etc) and common tool outputs (GATK, Salmon, OncoKB, VEP, etc.) preferred.

Preferred Skills:

  • Development with professional software development systems and methods (e.g. IDE's, ticketing systems, version control systems).

  • Familiarity with large public/private genomic data sets (GDC, TCGA, etc.).

  • Familiarity with clusters, containers, and cloud computing infrastructure for data processing, analysis, and storage.

  • Experience in tools to analyze cancer genomics datasets (GATK, Salmon, OncoKB, VEP, etc.).

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