[May 8: I just learned of this DOE funding opportunity with pre-applications due June 3: Mathematical and Statistical Methodologies for DOE Data-Centric Science at Scale http://www.science.doe.gov/grants/pdf/SC_FOA_0000918.pdf.]
The Department of Energy Office of Science (DOE SC) just announced a funding opportunity for uncertainty quantification methodologies for enabling extreme-scale science with pre-applications required and due April 24.
The funding opportunity announcement (FOA) summary states they invite "applications for basic mathematical, statistical and computational research that significantly advances uncertainty quantification methodologies for enabling extreme-scale science." The summary goes on to state that the DOE SC Advanced Scientific Computing Research (ASCR) Applied Math subprogram invites applications in basic research that:
significantly advance uncertainty quantification (UQ) methodologies as an enabling technology in extreme-scale scientific computing. UQ broadly refers to the end-to-end study of the accuracy, reliability, development and effective use of computational models in making scientific inferences. Mathematically rigorous UQ methodologies are essential to a wide range of DOE science and engineering applications in carrying out predictions, design optimization, decision making, or other high-level tasks. UQ relies on a broad range of applied mathematics and statistics research, along with algorithmic and computational developments, and subject matter expertise, to enable an appropriate level of confidence in the use of computational models for scientific investigations.
The computational science and engineering community understands the importance of uncertainty quantification, and key principles, best practices, and tools have been developed and are evolving for predictive science and engineering. At the same time, the nature of high-performance scientific computing research and practice is expected to be fundamentally different given the forecasts for disruptive changes in computing architectures and technologies in this decade. This FOA calls for basic research in methodologies and tools that will deliver significantly improved or advanced UQ capabilities for DOE-mission science based on anticipating the characteristics and challenges, and fully realizing the potential advantages, of using extreme-scale computing systems.
See the
FOA more more information.
See also the
FOA FAQ.
Some of you may note that this is my first blog entry to publicize a specific funding opportunity (although I did write
White House OSTP "Big Data" Initiative Includes Opportunities for Statistics.) I'm making this exception because this is the first FOA from DOE Science that has been shared with the ASA and it seems like an FOA ideally suited to statisticians. We hope DOE Science receives a strong response to this FOA from the statistical community and that there will continue to be FOAs from DOE Science that tap the expertise of statisticians.
For more on funding opportunities, see this ASA webpage,
Non-ASA Sources of Potential Funding, maintained by the
ASA Committee for Funded Research.
By the way, the ASA Committee of Funded Research is planning to establish a listserve to share such funding opportunity announcements. To be included, or to offer suggestions for how best to communicate funding opportunities to ASA members, please
email me. [4/17 update: ASA Director of Programs Lynn Palmer has created an ASA Community group,
Funding Opportunities. Please join that group by logging into the
ASA Community and following the standard procedure for joining a group. Email me for any help.]
We are also considering question and answer (Q&A) pieces with funding agency program officers. Please
email me any suggested questions or agencies beyond NSF, NIH, and Department of Energy.
See
other ASA Science Policy blog entries. For ASA science policy updates, follow @ASA_SciPol on Twitter.