Postdoctoral Associate - Getz Lab

The Getz Lab (at the Broad Institute and MGH) is a worldleading laboratory for cancer genome analysis. We develop highly innovative robust and widelyused computational methods to study the molecular basis of cancer including genomic alterations that drive primary and resistant tumors celloforigin 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 toptier 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.

Getz Lab website:

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 skillbuilding opportunities.

The lab is engaged in the larger Bostonarea 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 wetlab 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 researcher to explore disease progression in several blood cancers. This could include such projects as (i) investigating the clonal kinetics of Chronic Lymphocytic Leukemia (CLL) after therapeutic treatment and in cases of spontaneous disease regression; and (ii) characterizing the drivers of transformed Follicular Lymphoma (tFL) through analysis of spatial profiling of the FL microenvironment integrated with analysis of whole genome sequencing 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 creativityour best assetcreates an excellent environment for deep innovation outofthebox 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 worldclass dynamic team!


Role Expectations
Play a lead role in designing and executing data analysis strategies to support research projects
Explore and develop tools for analyzing novel data types.
Develop new spatial and genomic analysis 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 noncomputational researchers.
Prepare written reports (e.g. manuscripts grants patents) and presentations for meetings.
Opportunity to teach and mentor junior team members.


Requirements
A PhD in Bioinformatics Computer Science Engineering Mathematics Statistics Physics Population Health or a related quantitative discipline
Fast learner analytical thinker creative handson teamplayer.
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 modelsTumor Microenvironment

Twitter: @getzlab

Hashtags: #interdisciplinary #collaborate #cancergenomics #computationalmodels #MGHCancerCenter #Broadinstitute #AI