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
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
Associate Computational Biologist II
Founder of CDS
Director of Data Science, Generate Biomedicines
Senior Scientist, Merck
Senior Computational Associate
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
We are an interdisciplinary group dedicated to accelerating cancer research. We help design and analyze large-scale experiments, develop new statistical tools and machine learning methods, write papers, produce datasets used by tens of thousands of researchers around the world, and guide research and development for applying new technologies to cancer research.
The success of cancer precision medicine requires determining optimal treatments given the detailed genomic and molecular information encoded in each patient’s tumor. CDS aims at accelerating precision cancer medicine by creating computational software (such as Chronos) and interactive exploratory tools (such as the DepMap portal) to help researchers understand the mechanisms of genetic and chemical vulnerabilities across all human cancers. To achieve this, CDS collaborates with multiple groups and research labs (e.g., DepMap, PRISM, CCLF, Sellers Lab, Getz lab etc) to assemble the most detailed and comprehensive characterization of the genomic and molecular features of preclinical cancer models.
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 strong connections, 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, and clinicians.
We are seeking a highly motivated and talented individual to lead bioinformatic engineering efforts in CDS and create a world-class suite of data analysis pipelines. This is an exciting opportunity to work closely with a diverse team of computational biologists, clinical oncologists, experimental scientists, and scientific leaders both within the Broad and within industry.
We are seeking motivated computational biology leader to direct our efforts in target identification/exploration and predictive modeling for cancer dependencies/vulnerabilities including integration of advanced ‘omic characterization of cell line models. You will drive and implement the data science strategy for new target identification and evaluation through integration of dependency data with deep ‘omics profiling and will work collaboratively in the world-class research environment of the Broad Institute Cancer Program with cancer biologists, other data scientists, and industry partners.
Email: contactcds at broadinstitute.org