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. 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 , and read press releases for a recent suite of papers from the Pan-Cancer Analysis of Whole Genomes project in Nature and one for our 2019 study of somatic mutations in normal tissues in Science ). 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 : Our lab is comprised of 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 : We are seeking a highly motivated, creative, and talented researcher to explore the underlying mechanisms of cancer evolution and response or resistance to therapy. We envision this team member taking a lead role in (i) examining genomic data (including somatic and germline events at the DNA, RNA, and protein level) in both tumor and normal samples; and (ii) interpreting these and clinical data across a set of individuals (populations or cohorts). These efforts will contribute to understanding cancer initiation and progression, pinpointing novel therapeutic targets, and uncovering disease subtypes for eventual clinical benefit.
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!
Play a lead role in designing and executing data analysis strategies to support research projects involving multiple data types.
Explore and develop tools for analyzing novel data types.
Develop new methodologies for integrating data and predicting tumor outcome, subtypes, molecular mechanisms, and response to therapy.
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 mentor junior team members.
A PhD in Bioinformatics, Computer Science, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline
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 or biology is a plus.
Knowledge of cancer genomics is a plus but is NOT required. Inclination to acquire such knowledge is imperative.
Keywords: Cancer, Personalized Medicine, Genomics, Machine Learning, Computational biology, Statistics, Cancer resistance, Biomarker discovery, Computational modeling, Tumor evolution, Predictive models, Single-Cell Sequencing, RNA sequencing, Experimental validation, Tumor Microenvironment, Early Detection, Mutational Signatures, Pre-malignant somatic mutations, Cancer Cell-of-origin, Aging
Hashtags: #interdisciplinary #collaborate #cancergenomics #computationalmodels #RNAseq #MGHCancerCenter #Broadinstitute #AI
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.