News

Keep up with the latest news from the NCI Center for Biomedical Informatics and Information Technology (CBIIT) and the data science communities.

An NCI-funded technology blends specific molecular markers along with traditional morphological features in the same cells and in one digital slide. This tool could someday help pathologists and ML models better predict cancer treatment response and outcomes.

Are you interested in using spatial omics and single-cell approaches in your cancer research? Participate in the HTAN Data Jamboree, where you'll work with a team to build unique solutions that solve problems in cancer research. Submit your application by September 6.

Help define the data standards that will make data in the USCDI+ Cancer Registry interoperable with data collected for clinicals, public health, and research. Submit your feedback by Monday, September 23, 2024.

If you’re a new investigator eager to start your independent career, check out this opportunity from NIH. This award might be the perfect fit!

The funding opportunity aims to support Research Software Engineers in developing and disseminating biomedical, behavioral, or health-related software, tools, and algorithms.

An international team of researchers combined genomics, biopsy results, and artificial intelligence (AI) to track prostate cancer over time. Learn more about these “evolvability” metrics and how they could someday help predict cancer re-occurrence.

If you’re working with NIH genomic data, you’ll need to be aware of some new security requirements for data management and access that take effect on January 25, 2025. Learn more about how this could impact your work.

Want to pursue a career opportunity in data science with NCI? Browse through federal and contractor roles, fellowships, and internships in our recently launched employment section!

NIH has a new funding opportunity to help you develop robust, re-usable scientific software and tools to advance cancer research.

NCI-funded researchers are blending mathematics with machine learning to refine cancer treatment. In the future, this kind of virtual tumor model could help to further personalize care for people with cancer.