Advancing Research at the Intersection of Biology and Artificial Intelligence/Machine Learning (AI/ML)

Advancing Research at the Intersection of Biology and Artificial Intelligence/Machine Learning (AI/ML) is sponsored by National Science Foundation (NSF) BIO. NSF BIO supports research combining biology and AI/ML to advance biological discovery or develop AI/ML methods inspired by biological systems, encouraging interdisciplinary collaboration.

This includes research related to biomedical devices (from imaging through medical devices) and systems.

Advancing Research at the intersection of Biology and Artificial Intelligence/Machine Learning (AI/ML) | NSF - U.S. National Science Foundation Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements .

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Advancing Research at the intersection of Biology and Artificial Intelligence/Machine Learning (AI/ML) Encourages proposals that advance biological research through use of Artificial Intelligence/Machine Learning (AI/ML) or through development of AI/ML methods using biological data and systems in areas supported by the Biological Sciences Directorate.

Encourages proposals that advance biological research through use of Artificial Intelligence/Machine Learning (AI/ML) or through development of AI/ML methods using biological data and systems in areas supported by the Biological Sciences Directorate.

The U.S. National Science Foundation Directorate for Biological Sciences (NSF BIO) encourages the submission of proposals that advance biological research using Artificial Intelligence/Machine Learning (AI/ML) or AI/ML methods using biological data and systems. To tackle grand challenge problems across the biological sciences, researchers increasingly are turning to the development and adoption of AI/ML methods.

AI/ML includes any computational tool that mimics intelligence and the ability to learn from data to derive inferences. These methods are powerful tools for analyzing, synthesizing, and integrating large and complex datasets, developing predictive models, and designing and deploying bio-inspired innovations.

Unique aspects of information processing in biological systems and the complexity of biological data can also inform and inspire new developments in AI/ML. In addition, AI-enabled research requires a trained workforce prepared to use, develop, and validate appropriate AI/ML approaches and supporting technologies tailored for biological systems.

To promote research that benefits from AI/ML and reduces barriers to its use in the biological sciences, NSF BIO welcomes proposals that incorporate, develop, or advance AI/ML approaches across the research areas supported by the BIO Directorate. Proposers are encouraged to include partnerships between biologists and experts in AI/ML from academia, industry, or other organizations.

Areas where AI/ML approaches may be used include, but are not limited to: Implementing existing AI/ML methods to solve pressing questions in biology Developing new AI/ML models to derive biological insights Validating and/or comparing results from AI/ML methods against results from traditional analytical methods, theoretical models, and/or experimental approaches Proposals that advance both biological discovery and AI/ML research are especially encouraged.

Activities, such as generating well-curated and labeled, publicly available AI/ML training datasets, creating software and tools openly available to the scientific community, and developing a workforce trained and conversant in AI/ML approaches may be incorporated as elements relevant to the Intellectual Merit and/or Broader Impacts of proposals in response to this call. Proposals solely aimed at generating new data are not encouraged.

NSF offers access to computing resources through the National Artificial Intelligence Research Resource (NAIRR) Pilot for the research community to request access to a set of computing, model, platform, and educational resources for projects related to advancing AI research. This is not a special competition or new program. Relevant proposals should be submitted to an existing NSF BIO solicitation.

Proposal titles should begin with " BIO-AI: " followed by any other relevant prefixes and the project name. Before submission, PIs are encouraged to contact bio-ai@nsf. gov to discuss the appropriate mechanism for submission.

Proposals will be evaluated alongside other proposals submitted to the respective BIO unit and therefore must be responsive to the relevant solicitation. Proposals must also describe the AI/ML methods and justify how these methods address a scientific challenge or question that was previously intractable.

The project team must have appropriate expertise in AI/ML, which can be demonstrated through previous experience with proposed methods, collaboration with relevant experts, and/or pathways for training students and other researchers in AI/ML. General questions about this Dear Colleague Letter or specific questions about fit of the proposed research to this opportunity may be submitted to bio-ai@nsf. gov .

Assistant Director for Biological Sciences Directorate for Biological Sciences (BIO)