Opportunity Information: Apply for 21 530
The Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science opportunity is an interagency grant solicitation led by the National Science Foundation (NSF) that focuses on pushing forward ambitious, high-risk, high-reward research at the intersection of advanced computing and real-world health challenges. The core idea is to fund interdisciplinary teams that can deliver transformative advances in areas like artificial intelligence, data science, computer and information science, engineering, mathematics, statistics, and behavioral or cognitive science, specifically when those advances help answer urgent biomedical and public health questions. Rather than incremental improvements, the solicitation emphasizes breakthroughs that can change what is possible in how health-related data is captured, linked, understood, and used to improve outcomes.
A central theme is building new ways to "intuitively and intelligently" collect, sense, connect, analyze, and interpret data coming from individuals, devices, and larger systems. That includes data streams such as wearables and sensors, clinical and public health records, imaging, lab results, environmental measurements, and other sources that are often fragmented or difficult to integrate. Projects are expected to move beyond simply applying existing tools; the program is looking for novel methods and foundational innovations that make it easier to derive reliable insights from complex, messy, multi-scale, and sometimes real-time data. In practical terms, that could mean new algorithms for learning from limited or biased datasets, more robust approaches for integrating heterogeneous data sources, methods that support earlier detection or better prediction of disease, or systems that enable personalized or adaptive interventions.
The solicitation also makes it clear that success depends on teams that genuinely span disciplines. The biomedical or public health problem is not treated as a backdrop; it is the driver for new fundamental research in computing and related fields, and the expectation is that teams will be prepared to tackle both sides at once. The work should advance underlying scientific and engineering knowledge while also making progress on concrete health questions, such as improving diagnosis, optimizing treatment decisions, strengthening population health monitoring, or enabling better prevention strategies. Because the problems are complex and high stakes, the program encourages creative approaches that may be technically challenging but potentially game-changing.
From the funding details provided, this is a discretionary grant opportunity (Funding Opportunity Number 21-530) in the science and technology research and development category. The ceiling amount per award is listed as $1,200,000, with an expected total of 16 awards, indicating a competitive program designed to support a limited number of substantial, research-intensive projects. The opportunity was created on November 20, 2020, with an original closing date of February 16, 2021. While the listed deadline is historical, the summary still reflects how the program is structured and what it values: transformative interdisciplinary research that leverages AI and advanced data science to improve biomedical and public health discovery and decision-making.
Eligibility is described as "Others (see text field entitled Additional Information on Eligibility for clarification)," which implies that applicants needed to consult the full solicitation for specifics on who could apply (for example, different institution types, collaborations, or other requirements). The CFDA numbers span both NSF and multiple health-related research programs, reinforcing that this is interagency in nature and that proposals are expected to sit at the boundary between core computational innovation and meaningful health impact.
Overall, the opportunity is aimed at researchers who can demonstrate both a compelling health-related use case and a credible plan to invent or significantly advance the computational, statistical, engineering, or behavioral science methods needed to solve it. The strongest projects, by the program’s own framing, would be those that create new capabilities for connected health data ecosystems and deliver insights that help enable discovery and optimize health, while also contributing lasting advances to the fundamental sciences and engineering disciplines that underpin smart health technologies.Apply for 21 530
- The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.041, 47.049, 47.070, 47.075, 93.172, 93.173, 93.213, 93.242, 93.279, 93.286, 93.361, 93.396, 93.846, 93.847, 93.853, 93.859, 93.865, 93.866, 93.867, 93.879.
- This funding opportunity was created on Nov 20, 2020.
- Applicants must submit their applications by Feb 16, 2021. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $1,200,000.00 in funding.
- The number of recipients for this funding is limited to 16 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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Frequently Asked Questions (FAQs)
What is the "Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science" opportunity?
It is an interagency grant solicitation led by the National Science Foundation (NSF) focused on advancing ambitious, high-risk, high-reward research at the intersection of advanced computing and real-world biomedical and public health challenges. The solicitation emphasizes transformative, interdisciplinary work rather than incremental improvements.
Who leads this grant solicitation?
The solicitation is led by the National Science Foundation (NSF) and is described as interagency in nature, meaning it is aligned with multiple health-related research programs in addition to NSF interests.
What is the Funding Opportunity Number (FON) for this program?
The Funding Opportunity Number is 21-530.
What type of funding opportunity is this?
It is a discretionary grant opportunity in the science and technology research and development category.
What is the main goal of the program?
The main goal is to fund interdisciplinary teams that can produce breakthrough advances in AI, advanced data science, computing, and related foundational areas, specifically when those advances help answer urgent biomedical and public health questions and improve discovery and decision-making.
What kinds of research does the solicitation prioritize?
The solicitation prioritizes transformative research that creates new capabilities for capturing, linking, understanding, and using health-related data. It is looking for novel methods and foundational innovations, not just applications of existing tools.
Does the program prefer incremental improvements or breakthrough innovations?
Breakthrough innovations. The solicitation emphasizes ambitious, high-risk, high-reward work intended to change what is possible in smart health and biomedical research.
What disciplines are expected to be involved?
Projects are expected to involve genuine interdisciplinary teams spanning fields such as artificial intelligence, data science, computer and information science, engineering, mathematics, statistics, and behavioral or cognitive science, connected directly to biomedical and/or public health research questions.
How important is the biomedical or public health problem in the proposal?
It is central. The biomedical or public health problem is not treated as a backdrop; it is the driver for new fundamental research in computing and related fields. Teams are expected to tackle both the health challenge and the foundational methods at the same time.
What kinds of data sources does the program consider relevant?
The solicitation references diverse and often fragmented data streams, including wearables and sensors, clinical and public health records, imaging, lab results, environmental measurements, and other sources that may be difficult to integrate.
What does the solicitation mean by collecting and interpreting data "intuitively and intelligently"?
It points to building new ways to collect, sense, connect, analyze, and interpret data from individuals, devices, and larger systems, including methods that can handle complex, messy, multi-scale, and sometimes real-time data.
What kinds of technical contributions might fit this program?
Examples described in the summary include new algorithms for learning from limited or biased datasets, more robust approaches for integrating heterogeneous data sources, methods that support earlier detection or better prediction of disease, and systems that enable personalized or adaptive interventions.
Is simply applying existing AI tools to health data likely to be competitive?
The program description suggests that projects are expected to move beyond applying existing tools. It emphasizes novel methods and foundational innovations that advance underlying scientific and engineering knowledge while addressing a concrete health problem.
What types of health outcomes or use cases are mentioned?
The solicitation mentions health-related goals such as improving diagnosis, optimizing treatment decisions, strengthening population health monitoring, and enabling better prevention strategies.
What is the maximum award amount (ceiling) per project?
The ceiling amount per award is listed as $1,200,000.
How many awards are expected?
The opportunity indicates an expected total of 16 awards.
When was this opportunity created?
The opportunity was created on November 20, 2020.
What was the closing date for submissions?
The original closing date listed is February 16, 2021. This deadline is historical in the provided information.
Does the historical deadline change what the program values?
Even though the listed deadline is in the past, the summary describes the program structure and priorities: transformative interdisciplinary research leveraging AI and advanced data science to improve biomedical and public health discovery and decision-making.
Who is eligible to apply?
Eligibility is listed as "Others (see text field entitled Additional Information on Eligibility for clarification)," indicating that applicants were expected to consult the full solicitation for specific eligibility details.
What does it mean that eligibility is listed as "Others"?
It implies that eligibility may depend on conditions described in the full solicitation (for example, eligible institution types, collaboration requirements, or other criteria), but those specifics are not included in the summary provided here.
What does "interagency" imply for this program?
It implies the solicitation spans NSF and multiple health-related research programs, reinforcing that proposals are expected to sit at the boundary between core computational innovation and meaningful health impact.
What are CFDA numbers and what do they indicate here?
The summary notes that CFDA numbers span NSF and multiple health-related research programs. Based on the provided description, this is used to reinforce the interagency nature of the opportunity and the expectation of proposals that combine foundational computing advances with biomedical/public health relevance.
What would a strong proposal look like based on the description?
A strong proposal would present (1) a compelling, urgent health-related use case and (2) a credible plan to invent or significantly advance the computational, statistical, engineering, and/or behavioral science methods needed to solve it, producing both health impact and lasting fundamental advances.
What kinds of challenges is the program trying to address in health data?
The program is trying to address challenges such as fragmentation across sources, difficulty integrating heterogeneous data, messy or biased datasets, and the need to derive reliable insights from complex, multi-scale, and potentially real-time information.
Is team interdisciplinarity optional or required?
The program description makes interdisciplinarity a central expectation. It indicates that success depends on teams that genuinely span disciplines and can handle both the computational innovation and the biomedical/public health problem together.
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