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Emerging Mathematics in Biology (eMB)

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NSF 25-509

Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Supports integrative research that develops advanced mathematical theories and methods to address complex biological challenges, thereby enhancing our understanding of diverse biological systems and informing public health policy.

Supports integrative research that develops advanced mathematical theories and methods to address complex biological challenges, thereby enhancing our understanding of diverse biological systems and informing public health policy.

Synopsis

The Emerging Mathematics in Biology (eMB) program seeks to stimulate the development of innovative mathematical theories, techniques, and approaches to investigate challenging questions of great interest to biologists and public health policymakers. It supports truly integrative research projects in mathematical biology that address challenging and significant biological questions through novel applications of traditional, but nontrivial, mathematical tools and methods or the development of new mathematical theories particularly from foundational mathematics, including the mathematical foundation of Artificial Intelligence/Deep Learning/Machine Learning (AI/DL/ML) enabling explainable AI or mechanistic insight. The program emphasizes the uses of mathematical methodologies to advance our understanding of complex, dynamic, and heterogenous biological systems at all scales (molecular, cellular, organismal, population, ecosystems, evolutionary, etc.).

 

Program contacts

Name Email Phone Organization
Zhilan J. Feng
Program Director
zfeng@nsf.gov (703) 292-7523 MPS/DMS
Julie B. Kellner
Program Director
jkellner@nsf.gov (703) 292-4834 BIO/IOS
David J. Klinke
Program Director
dklinke@nsf.gov (703) 292-2890 BIO/MCB
Jeremy Wojdak
Program Director
jwojdak@nsf.gov (703) 292-8781 BIO/DEB
Jennifer W. Weller
Program Director
jweller@nsf.gov (703) 292-2224 BIO/DBI

Awards made through this program

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