Computational Scientist I Getz Lab

Overview: The Getz Lab (at the Broad Institute and MGH) is a world-leading laboratory for cancer genome analysis. We develop highly innovative robust and widely-used computational methods to study the molecular basis of cancer including genomic alterations that drive primary and resistant tumors cell-of-origin premalignant lesions mutational processes activity of different pathways and microenvironmental changes. The Getz has developed many of the landmark statistical methods widely used by the field for (i) calling somatic mutations (ii) identifying genomic alterations that drive cancer (iii) mathematically modeling tumor evolution and (iv) identifying the genetic causes of therapeutic resistance among many other contributions. Our lab has close collaborations with dozens of leading clinicians and experimental researchers in Boston-area hospitals and elsewhere allowing us to generate new genomic data and from patients samples from a wide variety of disease settings and therapeutic trials. While the comprehensive analysis of cancer genomes is ongoing major barriers still exist in converting this information to patient benefit and achieving the goal of personalized medicine.

Our work stands at the forefront of cancer genome science and our research is regularly published in top-tier journals (see our work onGoogle ScholarandPubMed). We are dedicated to innovating and pushing the limits of what we know and what can be known in understanding the complexities of human cancer. Read more about us and our work at our website: .

Our ideal Computational Scientist candidate: We are currently seeking a highly motivated and talented individual with a strong computational and statistical background with demonstrated experience in the genomics/biological field. This Computational Scientist will be the computational lead in 2 independent collaborative projects that we have with industry partners over the next 2 years (with a potential for follow-on work beyond the next 2 years). In both of these projects we are exploring questions around the genomic mechanisms underlying the development of resistance to therapy in order to understand how to prevent or mitigate resistance development and maximize the clinical benefit of these agents in cancer patients. One of these projects focuses on understanding resistance development to newer antibody-drug conjugate (ADC) therapies in breast cancer and the other project focuses on understanding mechanisms of resistance to small molecule inhibitors in gastrointestinal (GI) cancers to guide development of combination therapy strategies that can prevent or mitigate this resistance. Within these projects there will be exciting opportunities to analyze patient cohorts with longitudinal datasets as well as help develop and improve computational methodologies approaches and tools to most effectively analyze these terms of preferred timing to onboard onto these projects the ideal candidate would be available to start early 2026 preferably by March 2026.

Environment/Lab Culture: Our lab brings together an interdisciplinary group of scientists engineers and clinicians who work together in a mutually supportive and respectful environment. Ideas are freely shared and contributions are highly valued.

Moreover Dr. Getz places a high priority on career development and his lab as well as the environments at the Broad Institute and Massachusetts General Hospital provide frequent and varied educational and skill-building opportunities.

The lab is engaged in the larger Boston-area ecosystem and the cancer research community worldwide and provides a vibrant research environment for your contributions to be disseminated and recognized in the field. Integrating our groups computational expertise with our collaborators in vitro cell line-based assay capabilities enables us to address key questions at a deeper and more impactful level. Indeed we constantly use and develop new tools and technologies to help unlock new findings.

As a member of our team and these projects you will collaborate with other academic and industry scientists engineers and clinicians in a collegial work environment with an emphasis on intellectual rigor. Indeed our collective brainpower and creativityour best assetcreates an excellent environment for deep innovation out-of-the-box thinking and creative problem solving. This position may be ideal for applicants looking to further their expertise in state-of-the-art cancer genomics or for those looking to apply and acquire knowledge across different disciplines in a stimulating and supportive environment. We encourage you to bring your energy expertise and talents to this world-class dynamic team!


Role Expectations

• Demonstrate initiative in completing projects independently effectively utilizing available resources and seeking guidance when appropriate.
• Design and execute data analysis strategies to support multiple data types.
• Ability to explore and develop tools for analyzing novel data types.
• Conduct QC analysis of data identify technical bottlenecks or challenges and implement solutions to overcome these barriers.
• Build and run pipelines for analysis of whole-genome sequences (WGS) bulk RNA sequencing single-cell/single-nucleus RNA sequencing etc. Such analysis includes discovery of mutations phylogenetic analysis of tumor evolution during the development of resistance detection of differentially expressed genes and pathways detection of expression modules etc.
• Develop methods to rank candidate targets based on suitability for therapeutic targeting.
• Effectively communicate research findings and ideas to diverse audiences within the Getz lab and external clinical collaborators both verbally and in writing.
• Ability to critically evaluate new scientific findings within the context of existing dogma and effectively summarize ideas to make significant contributions to scientific publications presentations grants and patents.
• Serve as a project lead for the computational aspects of both projects.
• Mentor and teach junior team members.

• A PhD in Math Biology Computer Science Physics Statistics Engineering or a related discipline is required. Postdoctoral experience is a plus.
• Experience with computational analysis algorithm development statistics and machine learning.
• Experience analyzing bulk and single cell human genomic and transcript data.
• Proficiency in at least one modern programming language. Experience in python is preferred.
• Strong verbal and written communication skills.
• Demonstrated ability to drive projects to completion evidenced by first-author or significant co-author contributions to accepted peer-reviewed manuscripts in quality scientific journals.
• Demonstrated leadership skills as a project lead of computational projects.
• Experience and ability to meet defined project milestones.
• Background in genetics or biology especially in cancer genomics is preferred.
• Previous experience in industry is a plus.
• Experience in working with and mentoring junior scientists is a plus.