Computational Scientist - Getz Lab

Overview

The Getz Lab (at the Broad Institute and MGH) is a world-leading laboratory for cancer genome analysis. We develop innovative, robust, and widely-used computational methods to study the molecular basis of cancer, including genomic alterations that drive tumors, cell-of-origin, premalignant lesions, mutational processes, activity of pathways, and microenvironmental changes. Our lab has developed landmark statistical methods for calling somatic mutations, identifying genomic drivers, modeling tumor evolution, and identifying genetic causes of therapeutic resistance.

We collaborate with clinicians and experimental researchers to generate genomic data from patient samples across disease settings and trials. While cancer genome analysis is ongoing, major barriers remain in translating this information to patient benefit and personalized medicine. Our work is published in top-tier journals. Read more .

Our ideal Computational Scientist candidate is highly motivated with a strong computational and statistical background and demonstrated experience in genomics/biological research. This Computational Scientist will be the computational lead in two independent industry-collaborative projects over the next two years, with potential follow-on work. These projects explore genomic mechanisms underlying resistance to therapies to prevent or mitigate resistance and maximize clinical benefit in cancer patients.

One project focuses on resistance to newer antibody-drug conjugate (ADC) therapies in breast cancer; the other focuses on resistance mechanisms to small molecule inhibitors in gastrointestinal cancers to guide combination therapy strategies. The role includes opportunities to analyze longitudinal patient cohorts and to develop and improve computational methodologies, tools, and approaches for these data. Ideally, the candidate would start early 2026 (preferably by March 2026).

Environment/Lab Culture:
Our lab brings together an interdisciplinary group of scientists, engineers, and clinicians who work in a mutually supportive and respectful environment. Ideas are shared openly and contributions are valued. Dr. Getz places a high priority on career development, and the lab, along with Broad Institute and Massachusetts General Hospital, provides education and skill-building opportunities. The lab connects with the broader Boston-area ecosystem and the worldwide cancer research community, offering a vibrant environment for contributions to be disseminated and recognized.

We integrate computational expertise with collaborators’ in vitro capabilities to address questions deeply. We continually develop new tools and technologies to unlock new findings.

As a member of our team, you will collaborate with academic and industry scientists, engineers, and clinicians in a collegial environment that emphasizes intellectual rigor. This position may be ideal for applicants seeking to advance expertise in state-of-the-art cancer genomics or to apply and gain knowledge across disciplines in a stimulating environment. We encourage you to bring your energy, expertise, and talents to this world-class team.

Role & Responsibilities

• 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.
• Explore and develop tools for analyzing novel data types.
• Perform QC analysis of data, identify bottlenecks, and implement solutions.
• Build and run pipelines for analysis of whole-genome sequences (WGS), bulk RNA sequencing, single-cell/single-nucleus RNA sequencing, including discovery of mutations, tumor evolution phylogenetics, differential expression analysis, and pathway/module detection.
• Develop methods to rank candidate targets for therapeutic targeting.
• Communicate research findings clearly to diverse audiences within the lab and with external collaborators, both verbally and in writing.
• Critically evaluate new scientific findings and contribute to publications, presentations, grants, and patents.
• Serve as a project lead for the computational aspects of both projects.
• Mentor and teach junior team members.

Qualifications

• 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;
  Python is preferred.
• Strong verbal and written communication skills.
• Ability to drive projects to completion, evidenced by first-author or significant co-author contributions to peer-reviewed manuscripts.
• Demonstrated leadership as a project lead of computational projects.
• Experience meeting defined project milestones.
• Background in genetics or biology, especially cancer genomics, is preferred.
• Previous industry…