The Division of Radiation and Cancer Biology in the Department of Radiation Oncology at Stanford University seeks a Ph.D. to join the Department as an Assistant Professor in the Non-Tenure Line (Research). Stanford seeks applicants committed to developing an academic program focused on computational oncology in areas relevant to the field of radiation therapy (e.g. radiation biology, treatment response prediction, cancer immunology, cancer detection, etc.). Applicants must have completed a…Close
Register for the Data + AI Summit, June 27-30, 2022, San Francisco + Virtual! Registration is FREE for the world’s largest data and AI conference! View the agenda– four days packed with keynotes by industry visionaries, technical sessions, hands-on training, and networking. “Building the modern data stack with Lakehouse.”Close
Register to attend the 2022 Technology Showcase. The annual Technology Showcase, scheduled for September 7, 2022, will highlight how to work with the National Cancer Institute (NCI) and Frederick National Laboratory. It will feature technologies being developed at the NCI and FNL to encourage start-up company formation, technology licensing and collaborations.Close
Compete in the MICCAI 2022 Federated Learning Breast Density Challenge
Register for the Challenge: Submit your federated learning (FL) algorithm to the Breast Density FL Challenge! Data scientists, informaticists, and medical physicists are invited to develop the best, most generalizable models for breast density estimation using distributed or federated learning. During the challenge, participants will develop, train, and test models against digital mammographic imaging…Close
Two Opportunities with NIH’s AIM-AHEAD Coordinating Center
AIM-AHEAD Fellowship Program in Leadership Applications Now Open: The AIM-AHEAD Fellowship Program in Leadership will engage a diverse group of participants from under- represented populations to actively participate in mentored didactic and experiential educational activities…Close
Welcome to the Envisioning Computational Innovations for Cancer Challenges Hub Site
The Envisioning Computational Innovations for Cancer Challenges (ECICC) is dedicated to accelerating computational oncology and developing research collaborations across cancer and computational sciences. Scientists from over 200 organizations in academia, government, and industry have participated in multidisciplinary events to share their ideas and expertise, develop use cases, and explore new research collaborations.
Thanks to broader engagement with the research community, new resources and collaborative research opportunities developed by the NCI-DOE Collaboration are shaping the future of predictive oncology, drug discovery, and clinical applications!
We invite you to join us! To receive an invitation, please send an email to ECICC_Community@nih.gov.
The ECICC Community arose from the strategic interagency collaboration between the National Cancer Institute (NCI) and the Department of Energy (DOE), to simultaneously accelerate advances in precision oncology and computing.
A multidisciplinary, highly interactive Scoping Meeting was held to identify cancer challenge areas that push the limits of current cancer research computational practices and compel the development of innovative computational technologies:
- Generation of synthetic data sets for training, modeling and research
- Hypothesis generation using machine learning (ML)
- Creating digital twin technology
- Development of adaptive treatments
Download the Scoping Meeting Report.
Members of the ECICC Community published a commentary in Nature Medicine: "Digital twins for predictive oncology will be a paradigm shift for precision cancer care," which describes how digital twins can transform cancer care! Read the latest news on the Cancer Patient Digital Twin page.
On March 4, 2022, principal investigators from five cancer patient digital twin project teams reported on their project results, challenges and future work. Watch their presentations. These teams originated in July 2020 with the five-day virtual ideas lab, “Toward Building a Cancer Patient ‘Digital Twin." The event brought together a diverse group of researchers to form new collaborations and create innovative research projects that would advance the development of a cancer patient digital twin. In late 2020, these five project teams were selected to receive seed funding—made possible by DOE and NCI—through Frederick National Laboratory for Cancer Research. Three of those teams were also invited to apply for additional DOE funding.
Four Interactive, Multidisciplinary Workshops + a World Café* were held in March 2021 to help shape a “Blue-Sky” vision for the future of Radiation Oncology.
- For more information, Accelerating Precision Radiation Oncology through Advanced Computing and Artificial Intelligence
- A report from the meeting is featured in Radiation Research (April 2022).
NCI-DOE Collaboration Resources
For more information on the work of the NCI-DOE Collaboration, visit the website.
NCI-DOE Collaboration Publications
NCI-DOE Collaboration Resources
Interagency Modeling and Analysis Group (IMAG): IMAG is a government group of program officials from multiple federal government agencies supporting research funding for modeling and analysis of biomedical, biological and behavioral systems.
In May 2021, leaders of the NCI-DOE Collaboration presented at the American Association for Cancer Researchers (AACR) Annual Meeting. Watch the presentation.
1st MicroLab, June 2019: See information about our 1st Micro Lab
2nd MicroLab was held on September 25, 2019, 3:00 – 4:30 pm ET. Based on the breakout discussions from the first Micro Lab, participants developed use cases and identified critical next steps to shape future research in computational oncology! Download the presentations from the September 2019 Micro Lab on Cancer Challenges and Advanced Computing.
If you are interested in learning more or joining this multi-disciplinary community, please contact ECICC_Community@nih.gov.