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Cancer Genomics Jobs (NOW HIRING)

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX · On-site

$46K - $63K/yr

We combine cancer genomics, spatial multi-omics, advanced imaging, lineage tracing, and experimental model systems to uncover fundamental mechanisms governing cancer cell behavior, tumor evolution ...

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX

$46K - $63K/yr

We combine cancer genomics, spatial multi-omics, advanced imaging, lineage tracing, and experimental model systems to uncover fundamental mechanisms governing cancer cell behavior, tumor evolution ...

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How much do cancer genomics jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for cancer genomics in the United States is $21.34, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $23.56 per hour, depending on experience, location, and employer.

What is cancer genomics?

Cancer genomics is the study of the genetic mutations, alterations, and variations that occur in cancer cells. By analyzing the DNA and gene expression profiles of tumors, researchers and clinicians can better understand how cancers develop, grow, and respond to treatments. This field has led to the discovery of specific genetic drivers of cancer and enabled the development of targeted therapies, improving diagnosis, prognosis, and personalized treatment strategies for patients. Cancer genomics plays a crucial role in advancing precision medicine and improving outcomes for cancer patients.

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

To thrive as a Cancer Genomics Specialist, you need a solid background in molecular biology, genetics, and bioinformatics, often supported by an advanced degree (such as a PhD or MD) in a relevant field. Familiarity with next-generation sequencing (NGS) platforms, data analysis tools (like Python, R, or specialized genomics software), and certifications in molecular diagnostics are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills set top professionals apart in this field. These competencies are vital for accurately interpreting genomic data, collaborating with multidisciplinary teams, and driving personalized cancer treatment strategies.

What are some common challenges faced by professionals working in cancer genomics and how can they be addressed?

Professionals in cancer genomics often encounter challenges such as managing and interpreting large-scale genomic data, integrating findings with clinical information, and keeping up with rapidly evolving technologies. Effective collaboration with bioinformaticians, clinicians, and laboratory scientists is essential to ensure meaningful insights and successful application of genomic data in patient care. Addressing these challenges typically involves continuous learning, leveraging advanced data analysis tools, and participating in interdisciplinary team meetings to stay informed and aligned with best practices.

What is the difference between Cancer Genomics vs Cancer Bioinformatics?

AspectCancer GenomicsCancer Bioinformatics
Required CredentialsBiology, Genetics, Bioinformatics degrees, certifications in genomicsBioinformatics, Computer Science, Data Analysis certifications
Work EnvironmentResearch labs, hospitals, biotech companiesData analysis centers, research institutions, biotech firms
Industry UsageGenomic data collection, mutation analysis, cancer researchData processing, algorithm development, computational analysis
Common Search/ComparisonYesYes

While both roles focus on cancer research, Cancer Genomics primarily involves collecting and analyzing genomic data to understand cancer mutations. Cancer Bioinformatics emphasizes developing computational tools and analyzing large datasets to interpret genomic information. They often collaborate but serve different aspects of cancer research.

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Cancer Genomics jobs near you
Infographic showing various Cancer Genomics job openings in the United States as of August 2026, with employment types broken down into 98% Full Time, and 2% Contract. Highlights an 90% In-person, 2% Hybrid, and 8% Remote job distribution, with an average salary of $44,394 per year, or $21.3 per hour.

Scientist II, Cancer Genomics, Clinical Biomarker Development

Revolution Medicines

Redwood City, CA • Hybrid

Full-time

Posted 11 days ago

Job description

The Opportunity:

In this role you will join the Cancer Genomics group in Clinical Biomarker Development, which sits within the Translational Medicine department to develop biomarker, technology, and computational strategies for our RAS(ON) inhibitor programs. You will drive the application of advanced genomics analyses to maximize insight generation from clinical samples in our Phase I-III studies. This role offers the chance to work in a collaborative and innovative environment, including on cross-functional teams with other computational scientists, biomarker leads, biostatisticians, and preclinical scientists.

As a Cancer Genomics Scientist II in Clinical Biomarker Development, you will:

  • Apply advanced analytics and genomics solutions to clinical biomarker data to inform research & development.

  • Integrate multi-omics datasets to interrogate disease biology and prognosis, mechanisms of resistance, and predict drug response.

  • Collaborate with cross functional teams, managing interactions with key stakeholders to deliver robust biomarker analyses and recommend follow up actions.

  • Communicate results to expert and non-expert audiences, including internal cross-functional team members and external collaborators, through scientific publications and presentations.

Required Skills, Experience, and Education:

  • A Ph.D. in Cancer Genomics, Genetics, Computational Biology, Bioinformatics, or similar degree.

  • A minimum of 2 - 6 years post-PhD experience analyzing cancer genomics data (post-doc, biotech, pharma, diagnostics, or combination).

  • A strong foundation in cancer biology, preferably with an understanding of RAS/MAPK signaling pathways in pancreatic, lung, or colorectal cancer.

  • Proficiency programming in R and/or Python, and expert in clearly documenting work with a version control system (git).

  • Experienced in Linux and the cloud, including HPC clusters and command line interface, and developing genomics workflows for large scale NGS datasets.

  • Experienced analyzing ctDNA or other liquid biopsy data derived from blood samples.

  • Experienced in the interrogation of DNA sequence data derived from tumor tissue, such as gene-panel, whole-exome or whole-genome data and downstream analytics (clonality estimates, copy number variation, chromosomal instability, mutational signatures, etc).

  • Practiced in commonly used tools and methods for DNA data analysis (GATK, Bioconductor, etc) and in utilizing publicly available datasets (TCGA, cBioPortal) to interrogate cancer genomics data.

  • Strong understanding of statistics and the ability to generate robust predictive models with multidimensional data.

  • Strong interpersonal, verbal and written communication skills; proactive, self-motivated, and adaptable in a dynamic environment.

  • Demonstrated ability to translate complex data into clear biological insight, and to influence project direction through data-driven scientific inquiry.

Preferred Skills:

  • Experienced analyzing clinical endpoints (ORR, PFS, OS) including survival analysis.

  • Longitudinal ctDNA data analysis for predicting clinical endpoints (ORR, PFS, OS).

  • Deep knowledge of pancreatic, lung, or colorectal cancer, preferably including how progression, response and resistance may be mediated by biomarkers detected in tissue and/or blood biomarkers. 

    #LI-Hybrid #LI-EM1

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