Location: Houston, TX
Cap-Exempt H-1B Position — No lottery required
The University of Texas MD Anderson Cancer Center has the potential to unlock the power of data by further developing and investing in talent, team science and infrastructure to optimize multidimensional data integration, analysis and application for the benefit of patients with cancer. The Institute for Data Science in Oncology (IDSO) is a signature priority program aimed at transforming the patient experience, enhancing quality of life and accelerating scientific breakthroughs via advanced, data-driven approaches to cancer care. IDSO will enable teams to search for, learn from and apply as much information as possible gathered from every patient MD Anderson has seen or will see. By growing a data-centric culture and advancing data management and analytics maturity, we provide better, state-of-science and state-of-data-science care for patients while exploring areas of cancer research and treatment currently unknown to clinical communities. The IDSO recruits, positions and enables best-in-class data scientists to unravel seemingly insoluble problems in cancer and work toward meaningful solutions for patients. Our aims comprise reducing the time between diagnostic procedures and treatment decisions, advancing drug discovery efforts and bringing new, precise medicines to bedsides sooner. The IDSO centralizes our focused institutional investment in data science, as well as enables partnerships with other world-leading organizations, to operate and enhance an unprecedented oncological "data supply chain" designed to accelerate research and treatment innovation. Comprised of the best minds in a myriad of scientific and data-driven fields, the IDSO facilitates a culture grounded in our innovative "team-data science" principles, such as shared motivation, shared learning, provenance linking insights to observations and integrated data governance. One of the five focus areas IDSO has prioritized is Focus Area 2 - Single Cell Spatial Omics to Unveil Cancer Complexity, which