Emerging Mathematics in Biology
eMB grant funds innovative math research for biology to tackle complex biological questions using traditional/nontraditional methods & AI/math foundations.
This grant is no longer accepting proposals
U.S. National Science Foundation has archived this opportunity.
Funder: National Science Foundation
Due Dates: March 3, 2025 | March 1, 2026 (Annual)
Funding Amounts: $2M–$6M total for FY25–26; 10–15 awards/year; up to 3 years/project
Summary: Supports innovative mathematical research to address significant biological questions, including foundational work in AI/ML for biology.
Key Information: Proposals must include expertise in both mathematical and biological sciences; strong emphasis on integrative, cross-disciplinary research.
Description
The National Science Foundation's Emerging Mathematics in Biology (eMB) program aims to catalyze the development of innovative mathematical theories, techniques, and approaches to tackle complex and significant questions in biology and public health. The program supports integrative research projects that apply traditional or novel mathematical tools—including foundational mathematics for AI, deep learning, and machine learning—to advance understanding of dynamic, heterogeneous biological systems at all scales (molecular to ecosystem).
Research may focus on, but is not limited to:
- Mathematical foundations of AI/ML/DL in biomathematics, enabling explainable AI or mechanistic insight.
- Methods for modeling with limited, noisy, or heterogeneous data.
- Probabilistic and deterministic modeling frameworks in biology.
- Foundational mathematics in genomics and other -omics.
- Modeling organismal development, physiology, biomechanics, behavior, and neuroscience.
- Dynamics of interactions (e.g., host-symbiont, predator-prey, disease transmission).
- Environmental and evolutionary feedbacks.
- Mathematical tools for large biological datasets.
- Applications in biotechnology and climate impacts on biodiversity.
The program encourages new collaborations between mathematical, computational, and biological scientists, as well as innovative work by established interdisciplinary teams. Proposals should clearly articulate the biological significance, the mathematical challenges, and the necessity of mathematical approaches for advancing biological understanding.
