We build predictive models to predict cancer vulnerabilities from genomic profiles of tumors and cancer cell lines.
We integrate functional screening and 'omics data to identify novel cancer targets as well as drugs for repurposing.
We develop computational methods and tools to facilitate the analysis of CRISPR screening in cancer models.
We analyze highly-multiplexed small-molecule screening data from the PRISM platform to discover novel cancer therapeutic leads.
Director, Cancer Data Science
Associate Director
Computational Biologist
Group Leader, Computational Biology
Computational Scientist II
Associate Computational Biologist II
Software Engineer
Software Engineer
Senior Software Engineer
Bioinformatics Engineer
Software Engineer
Software Engineer
Associate Computational Biologist I
Associate Computational Biologist I
Associate Computational Biologist I
Leading Computational Biologist
Director of Data Science, Generate Biomedicines
Senior Computational Associate
Founder of CDS
MD-PhD Student, University of Pennsylvania
Granduate Student, Computational Biology, MIT
Neuroscience, UCSF
MD-PhD Student, Tri-Institutional Program
Sr. Visual Designer
Associate Professor, MD Anderson
Graduate Student, Genetics, Stanford University
Studying for AI Research
Computational Biologist, 10X Genomics
Graduate Student, Statistics, Duke University
Undergraduate Student, Stanford University
Graduate Student, Biomedical Informatics, Stanford University
Bioinformation Lead, Cancer Cell Line Factory
Medical Student, USC
Medical Student, Brown
Graduate Student, Computer Science, Princeton University
Graduate Student, Epidemiology, Harvard University
MD-PhD Student, Neuroscience, University of Pennsylvania
Graduate Student, Biomedical Sciences, UCSD
Graduate Student, Computer Science, University of Maryland
Associate Computational Biologist II
Medical Director, Genentech
Software Engineer
Senior Software Engineer
Senior Software Engineer
PhD Student, Bioinformatics and Integrative Genomics, Harvard University
Principal Scientist, Kojin Therapeutics
Research Scientist, Genomics, DeepMind
PhD Student, Biological and Medical Informatics; University of California San Francisco
Associate Computational Biologist II
The Cancer Dependency Map Project (DepMap), an ambitious collaborative effort launched by the Broad Institute’s Cancer Program, aims to systematically identify the genetic and chemical vulnerabilities across human cancers, along with the specific molecular features that can be used to predict which cancers will respond to a given treatment. Using a host of new technologies like CRISPR-based gene editing, pooled drug screening, and next-generation sequencing, we have deeply characterized over a thousand different cancer models and produced some of the largest cancer datasets in the world, which are now being widely used to identify new vulnerabilities in this devastating disease.
Despite the widespread impact of the DepMap project so far, many unanswered questions and critical challenges remain. Now we are poised to launch an exciting next phase of this effort, leveraging cutting-edge new technologies that can, for example, screen the vast space of perturbation combinations, characterize cellular responses with unprecedented detail and single-cell resolution, and leverage next-generation cancer models. To turn these huge, complex data into progress against cancer, we need computational scientists and software engineers. As a member of our team, you will develop new computational and software tools to empower the whole research community in the battle against cancer.
In the Cancer Data Science team we pride ourselves on the quality and rigor of our science, but just as much on our work culture. We believe in a team with a healthy work-life balance and a high degree of psychological safety. We look for candidates with diverse backgrounds, strengths, and perspectives, who are willing to challenge and be challenged. We are also a highly collaborative team, working closely with cancer biologists, experimentalists, project managers, clinicians, and others.
We are seeking an enthusiastic and talented scientist to lead our efforts to create an exciting next phase of the DepMap Portal. In this role, you will work closely with the DepMap scientific leadership to define the strategic vision for the DepMap portal and help shape its evolution for the benefit of the global scientific community.
We are seeking an exceptional software developer to join the Cancer Data Science group to build tools and portals. In the Cancer Data Science group, we leverage data science approaches to understand cancer biology and support translational efforts.
We are seeking motivated and talented computational scientists to help analyze and understand a range of new cutting-edge cancer datasets, including multi-modal genomics, high-throughput drug screening, single-cell profiling and functional genomics. Working closely with a diverse range of collaborators, you will use statistical and machine learning tools to identify and understand new cancer vulnerabilities, and help create the datasets and tools powering therapeutic discoveries across the cancer research community.
We are seeking an enthusiastic and experienced computational scientist to lead genomics analysis efforts in the DepMap project. You will lead a small team of computational scientists focused on generating world-leading genomic characterization of pre-clinical cancer models, and developing tools and methods for integrating these data with clinical cancer genomics.
Email: jmmcfarl at broadinstitute.org