Joint DMS/NLM Initiative on Generalizable Data Science Methods for Biomedical Research | 19 500

Opportunity Information: Apply for 19 500

The Joint DMS/NLM Initiative on Generalizable Data Science Methods for Biomedical Research is a collaborative grant opportunity led by the National Science Foundation (NSF), specifically its Division of Mathematical Sciences (DMS) within the Directorate for Mathematical and Physical Sciences (MPS), together with the National Library of Medicine (NLM) at the National Institutes of Health (NIH). The central purpose of the program is to fund the creation of new, broadly applicable (that is, generalizable) mathematical, statistical, and data-science methods that can tackle major biomedical and health research problems driven by complex data. Rather than focusing on one narrow biomedical application, the emphasis is on foundational approaches that can transfer across datasets, diseases, settings, and scientific domains, improving how biomedical research is analyzed and validated in many contexts.

A key idea behind this interagency partnership is that modern biomedical research increasingly depends on large-scale, high-dimensional, and heterogeneous data, and that progress is often limited by the lack of robust, theoretically grounded methods for inference, learning, uncertainty quantification, and reproducible analysis. NSF brings deep expertise and long-term investment in core mathematics and statistics, along with a strong culture of developing new theory and general methods. NIH, through NLM, brings a direct connection to biomedical data science needs, including practical constraints in biomedical workflows and urgent demands around reliability and reuse of results. By aligning these strengths, the initiative aims to generate methods that are both mathematically innovative and directly relevant to real biomedical data challenges.

The opportunity also highlights two broader goals that are especially important in biomedical research today: reproducibility and open science. In practice, this means proposed work is expected to strengthen the reliability of conclusions drawn from biomedical datasets and to support transparent practices that make methods, data workflows, and findings easier to verify and reuse. While the announcement text does not list specific required deliverables, the program rationale clearly signals interest in approaches that reduce brittleness, improve repeatability of analyses, and help the broader research community build on prior work rather than repeatedly reinventing tools for each new dataset.

From an administrative standpoint, this was a discretionary grant funding opportunity in the category of science and technology and other research and development. The funding opportunity title is "Joint DMS/NLM Initiative on Generalizable Data Science Methods for Biomedical Research" and it appeared under Funding Opportunity Number 19 500. The administering agency listed is the National Science Foundation, and the creation date was October 5, 2018, with an original closing date of January 16, 2019. The program anticipated making around 10 awards, with an award ceiling of $300,000 per award. The opportunity includes CFDA numbers 47.049 and 93.879, reflecting the joint NSF and NIH/NLM alignment. Eligibility was described as unrestricted (open to any type of entity), subject to any additional clarifications that might have appeared in the full eligibility text.

In summary, this initiative was designed to push beyond incremental, application-specific analytics and instead fund research that advances the mathematical and statistical foundations of biomedical data science. Its intended impact is to improve how biomedical knowledge is generated from data by enabling more reliable, reusable, and broadly applicable methods, while also encouraging interdisciplinary research and training at the intersection of quantitative sciences and biomedical/health domains.

• The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Joint DMS/NLM Initiative on Generalizable Data Science Methods for Biomedical Research" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.049, 93.879.
• This funding opportunity was created on Oct 05, 2018.
• Applicants must submit their applications by Jan 16, 2019. (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 $300,000.00 in funding.
• The number of recipients for this funding is limited to 10 candidate(s).
• Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.

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