Postdoctoral Associate - The Getz Lab

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. We then follow up key findings experimentally. 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 on Google Scholar and PubMed). 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.

Environment/Lab Culture:

We are 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 mentoring postdoctoral trainees to work toward achieving their career paths and goals, 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. Our ability to integrate both computational and wet-lab work enables us to address key questions at a deeper and more impactful level. Indeed, we constantly use and develop new technologies to help unlock new findings.

Our ideal postdoc candidate:

In a short-term position (spanning approximately three months during the Summer of 2026), we are seeking a highly motivated researcher with experience in studying clonal heterogeneity with respect to the development of resistance to therapy in lung cancer to be the computational analysis lead who will bring an ongoing study to completion. This project will be conducted in close collaboration with Dr. Justin Gainor's lab, a world-leading clinical research lab in lung cancer mechanisms at MGH. This postdoc will be responsible for performing computational analyses (e.g., characterization of genomic alterations, phylogenetic analysis, etc.), assembling and finalizing a manuscript for submission to a peer-reviewed journal, and working closely with a Clinical Fellow from the Gainor Lab in designing and implementing a related study from the same patient data.

As a member of our team, you will collaborate with other scientists, engineers, and clinicians in a collegial work environment with an emphasis on intellectual rigor. Indeed, our collective brainpower and creativity-our best asset-creates an excellent environment for deep innovation, out-of-the-box thinking, and creative problem solving. We will teach you what you do not yet know through mentoring, peer support, and many educational opportunities (e.g., floor talks, regular meetings, boot camps, journal clubs, conferences, etc.), and we will work together to make discoveries that help answer the most challenging questions in cancer.

The successful candidate will bring...

Strong computational and statistical skills (e.g., a background in Computational Biology, Biology, Machine Learning, Statistics, Medicine, Physics, Chemistry, Engineering, Mathematics, Computer Science, or other related fields) to the lab as well as enthusiasm for learning on the job. In return, you will develop many core competencies to prepare you for the next stages of your career. Come and bring your energy, intellectual curiosity, and computational skills/talents to this world-class dynamic team!

Role Expectations

• Play a lead role in designing and executing data analysis strategies
• Bring an existing project to completion by submitting finalized work to a peer-reviewed journal
• Conceive, implement, and test statistical models; analyze data from experiments.
• Present results to a variety of audiences, including non-computational researchers.
• Prepare written reports (e.g., manuscripts, grants, patents) and presentations for meetings.
• Opportunity to teach and train other team members.

• A PhD in Chemical Biology, Bioinformatics, Computational Biology, Computer Science, Machine Learning, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline
• Demonstrated experience in studying clonal heterogeneity with respect to the development of resistance to therapy in lung cancer
• Fast learner, analytical thinker, creative, "hands-on", team-player.
• Experience with computational analysis, algorithm development, and statistics.
• Proficiency in at least one modern programming language. Experience with a scientific programming environment (such as Python, R, or Matlab) is preferred.
• Strong communication skills.
• Background in machine learning and/or cancer genomics is a plus.