Computational and Data-Enabled Science and Engineering in Mathematical and Statistical Sciences (CDS&E-MSS)
| Name | Phone | Room | |
|---|---|---|---|
| Yong Zeng | yzeng@nsf.gov | (703) 292-7902 | DMS |
| Malgorzata Peszynska | mpeszyns@nsf.gov | (703) 292-2811 | DMS |
| Andrew D. Pollington | adpollin@nsf.gov | (703) 292-4878 | E 8451 |
PROGRAM GUIDELINES
Apply to PD 20-8069 as follows:
For full proposals submitted via FastLane:
standard NSF Proposal & Award Policies & Procedures Guide proposal preparation guidelines apply.
For full proposals submitted via Grants.gov:
the NSF Grants.gov Application Guide: A Guide for the Preparation and Submission of NSF Applications
via Grants.gov Guidelines applies.
(Note: The NSF Grants.gov Application Guide is available on the Grants.gov website and on the
NSF website at: http://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide)
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), is effective for proposals submitted, or due, on or after June 1, 2020. Please be advised that, depending on the specified due date, the guidelines contained in NSF 20-1 may apply to proposals submitted in response to this funding opportunity.
DUE DATES
Full Proposal Window
September 1, 2021
- September 15, 2021
September 1 - September 15, Annually Thereafter
SYNOPSIS
The CDS&E-MSS program accepts proposals that engage with the mathematical and statistical challenges presented by (1) the ever-expanding role of computational experimentation, modeling, and simulation on the one hand, and (2) the explosion in production and analysis of digital data from experimental and observational sources on the other. The goal of the program is to promote the creation and development of the next generation of mathematical and statistical software tools, and the theory underpinning those tools, that will be essential for addressing these challenges.
The research supported by the CDS&E-MSS program will aim to advance mathematics or statistics in a significant way and will address computational or big-data challenges. Proposals of interest to the program must include a Principal Investigator or co-Principal Investigator who is a researcher in an area supported by the Division of Mathematical Sciences. The program welcomes submission of proposals that include multidisciplinary collaborations or provide opportunities for training through research involvement of junior mathematicians or statisticians. This program is part of the wider NSF Computational and Data-enabled Science and Engineering (CDS&E) enterprise.
RELATED PROGRAMS
- Computational and Data-Enabled Science and Engineering
- Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science Phase I
- Software Infrastructure for Sustained Innovation
- NSF Graduate Research Fellowship Program
RELATED URLS
- Data-Enabled Science in the Mathematical and Physical Sciences
- Computational Science
- Discovery in Complex or Massive Datasets: Common Statistical Themes
- Inventing a New America through Discovery and Innovation in Science, Engineering, and Medicine
What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)