pioneering translational data science

to advance biology, medicine, healthcare, and the environment

News

01 Nov 2016

Join our Team

We are looking for problem solvers and analytical thinkers with highly technical backgrounds to join our team. Current openings include data engineers, devops engineers, and bioinformaticians working on critical initiatives in cancer, genomics, and environmental research. Check out our current openings.

14 November 2016

SuperComputing 2016

Stop by Booth #2611 at SuperComputing this year to see demonstrations of our datasharing technology. This open-source software powers numerous platforms including the Genomic Data Commons and a recently announced Blood Profiling Atlas.

17 October 2016

Blood Profiling Atlas

The University of Chicago will play a key role in a new Blood Profiling Atlas by providing the data-sharing technology. This is a public-private partnership of representatives from government, academic, pharmaceutical and diagnostic companies to jump-start the development of an open database for liquid biopsies with an initial blood-profiling pilot program.

01 November 2016

Volunteer Opportunities

Do you share our passion of using data science to make an impact on important problems? Consider joining our team as a volunteer to contribute in an area of your expertise and fuel your curiousity. Your generosity and support are critical to delivering on our ambitious mission. Join our mailing list to get updates on new events and opportunities.

06 June 2016

Vice President Joe Biden Visits CDIS

Vice President Joe Biden toured the Genomic Data Commons operations center at the University of Chicago in advance of his appearance to announce the project June 6 at the annual meeting of the American Society for Clinical Oncology.

08 September 2016

Harnessing the Power of Big Data in Fight Against Cancer

CDIS Director Robert Grossman was featured on WTTW for our work building the Genomic Data Commons. Watch the interview to learn how we're using about the power of datasharing toward democratizing the analysis of large cancer genomic datasets.