Opportunity Information: Apply for RFA HG 14 005
Apply for RFA HG 14 005
- The National Institutes of Health in the education environment food and nutrition health income security and social services sector is offering a public funding opportunity titled "Revisions to Add Biomedical Big Data Training to Active Institutional Training Grants (T32)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.113 Environmental Health 93.121 Oral Diseases and Disorders Research 93.172 Human Genome Research 93.173 Research Related to Deafness and Communication Disorders 93.213 Research and Training in Complementary and Integrative Health 93.233 National Center on Sleep Disorders Research 93.242 Mental Health Research Grants 93.273 Alcohol Research Programs 93.279 Drug Abuse and Addiction Research Programs 93.286 Discovery and Applied Research for Technological Innovations to Improve Human Health 93.307 Minority Health and Health Disparities Research 93.310 Trans NIH Research Support 93.361 Nursing Research 93.398 Cancer Research Manpower 93.837 Cardiovascular Diseases Research 93.838 Lung Diseases Research 93.839 Blood Diseases and Resources Research 93.846 Arthritis, Musculoskeletal and Skin Diseases Research 93.847 Diabetes, Digestive, and Kidney Diseases Extramural Research 93.853 Extramural Research Programs in the Neurosciences and Neurological Disorders 93.855 Allergy and Infectious Diseases Research 93.856 Microbiology and Infectious Diseases Research 93.865 Child Health and Human Development Extramural Research 93.866 Aging Research 93.867 Vision Research.
- This funding opportunity was created on Apr 22, 2014 and posted on Apr 22, 2014.
- Applicants must submit their applications by Jul 28, 2016. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $6,000,000.00 to eligible and selected applicants.
- The number of recipients for this funding is limited to 3 candidate(s).
- Eligible applicants include: Private institutions of higher education Native American tribal organizations (other than Federally recognized tribal governments) Public and State controlled institutions of higher education Others (see text field entitled Additional Information on Eligibility for clarification) Native American tribal governments (Federally recognized).
- Other Eligible Applicants include the following Alaska Native and Native Hawaiian Serving Institutions Asian American Native American Pacific Islander Serving Institutions (AANAPISISs) Hispanic serving Institutions Historically Black Colleges and Universities (HBCUs) Indian/Native American Tribal Governments (Other than Federally Recognized) Tribally Controlled Colleges and Universities (TCCUs) Only institutions with currently active T32 institutional training grants are eligible to apply for revisions (competitive supplements) for the expressed purpose of training the next generation of scientists who will develop computational and quantitative approaches and tools needed by the biomedical research community to work with biomedical Big Data in the biomedical sciences. The sponsoring institution must assure support for the proposed program. Appropriate institutional commitment to the program includes the provision of adequate staff, facilities, and educational resources that can contribute to the planned program. The applicant institution(s) must have a strong and high quality research program in biomedical Big Data Science that includes diverse and complex data types, such as genomic, other omic, imaging, phenotypic, exposure, etc., both in the basic and clinical sciences. The applicant institution(s) must have the requisite faculty and facilities to conduct the proposed institutional program. In many cases, it is anticipated that the proposed program will complement, but be distinct from, other ongoing research training programs occurring at the applicant institution. It is expected that a substantial number of program faculty will have active biomedical Big Data Science research projects involving a variety of data types in the basic and clinical sciences in which participating trainees may gain relevant experiences consistent with their research interests and goals.
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Opportunity Summary:
The NIH funding opportunity RFA-HG-14-005, titled "Revisions to Add Biomedical Big Data Training to Active Institutional Training Grants (T32)," is a discretionary grant announcement aimed at strengthening the biomedical research workforce by expanding existing NIH institutional training programs. Rather than creating brand-new T32 training grants, this FOA is specifically about competitive supplements (formal revisions to active awards) that allow institutions with currently funded T32 programs to add a dedicated "Big Data Science" training track. The central goal is to prepare a new generation of scientists who can design computational and quantitative methods, build tools, and develop technologies that help the biomedical community extract meaningful value from rapidly growing, increasingly complex biomedical data.
The opportunity is framed around the rising importance of biomedical big data and the practical challenges it creates for research. NIH is looking for training programs that can produce researchers capable of working across diverse data types and research settings, including both basic science and clinical science environments. The FOA emphasizes that modern biomedical data can include genomic and other "omics" data, imaging, phenotypic information, exposure-related data, and other complex datasets. The training track is meant to cultivate people who not only know how to analyze data, but who can also create new approaches and methods that make large-scale biomedical data more usable, interpretable, and actionable for discovery and translation.
Only institutions that already have an active NIH T32 institutional training grant are eligible to apply, since the mechanism is a revision/competitive supplement to an existing program. NIH expects strong institutional commitment to the proposed expansion, including adequate staffing, facilities, and educational resources. A key eligibility expectation is that the applying institution must already have a strong, high-quality research program in biomedical Big Data Science, with faculty who are actively engaged in big-data-driven biomedical research across multiple data types. This is important because NIH anticipates that trainees in the new track will gain hands-on, research-based experience by participating in active projects that align with their interests and career goals. In many cases, the FOA anticipates that the big data track will complement existing training activities at the institution, but still be meaningfully distinct rather than a minor relabeling of what already exists.
From a funding and scale standpoint, NIH listed an estimated total funding amount of $6,000,000 with an expectation of about three awards, indicating a relatively selective competition designed to support a small number of strong expansions. The FundingInstrumentType is a grant, and the broad FundingActivityCategory includes education as well as multiple health-related domains, which is reflected in the large set of CFDA numbers associated with different NIH institutes and research areas (ranging from human genome research to cancer, mental health, aging, cardiovascular disease, and more). That wide linkage signals that NIH views biomedical big data skills as a cross-cutting need that applies to many disease areas and scientific disciplines, not a niche specialty.
Eligible applicants include a wide range of higher education institutions and certain tribal organizations and governments, including public and state-controlled universities, private universities, and several categories of minority-serving institutions such as HBCUs, Hispanic-serving institutions, AANAPISIs, Alaska Native and Native Hawaiian-serving institutions, and tribally controlled colleges and universities. However, regardless of institutional type, the most important eligibility gate is still the presence of a currently active T32 award and the ability to demonstrate the necessary research depth, faculty expertise, and infrastructure to support rigorous training in biomedical big data science.
Administratively, the opportunity was posted and created on April 22, 2014, with a closing date of July 28, 2016, and an archive date of August 28, 2016, meaning it was time-limited and is no longer open. The sponsoring agency is the National Institutes of Health, and the announcement directs applicants and readers to the NIH Grants Guide page for full details. For technical issues accessing the announcement, NIH provided contact information through the NIH Office of Extramural Research (OER) webmaster.
In practical terms, this FOA was NIH's way of accelerating workforce development in data-intensive biomedical science by leveraging existing training structures. By funding supplements to active T32 programs, NIH could rapidly add specialized training capacity where strong training environments already existed, helping ensure that future biomedical researchers are prepared not just to handle big datasets, but to push the field forward by inventing better analytical methods, computational tools, and data-driven technologies.
FAQs: NIH RFA-HG-14-005 (Revisions to Add Biomedical Big Data Training to Active Institutional Training Grants (T32))
What is the funding opportunity RFA-HG-14-005?
RFA-HG-14-005 is an NIH discretionary grant announcement focused on strengthening the biomedical research workforce by expanding existing NIH institutional training programs. It supports formal revisions (competitive supplements) to active T32 awards so institutions can add a dedicated Biomedical Big Data Science training track.
Is this opportunity for new T32 training grants?
No. This funding opportunity is specifically for competitive supplements (revisions) to currently active NIH T32 institutional training grants. It is not intended to create brand-new T32 programs.
What is NIH trying to accomplish with this FOA?
The main goal is to train a new generation of scientists who can design computational and quantitative methods, build tools, and develop technologies that help the biomedical community extract meaningful value from rapidly growing and increasingly complex biomedical data.
What kind of training is NIH looking to add through these revisions?
NIH is looking for a distinct "Big Data Science" training track within an existing T32 program. The track should prepare trainees to work across diverse biomedical data types and research settings, including basic science and clinical science environments, and to develop new methods and approaches that make large-scale biomedical data more usable, interpretable, and actionable.
What does NIH mean by "biomedical big data" in this FOA?
The FOA frames biomedical big data broadly, including genomic and other "omics" datasets, imaging data, phenotypic information, exposure-related data, and other complex datasets that are large-scale and challenging to analyze and interpret.
Who is eligible to apply?
Only institutions that already have an active NIH T32 institutional training grant are eligible, because this opportunity funds revisions/competitive supplements to existing awards. The announcement also indicates eligibility for a wide range of higher education institutions and certain tribal organizations and governments, but the key eligibility requirement remains having a currently active T32 award.
Do minority-serving institutions and tribal entities qualify?
The eligible applicant types listed include several categories of minority-serving institutions (such as HBCUs, Hispanic-serving institutions, AANAPISIs, Alaska Native and Native Hawaiian-serving institutions, and tribally controlled colleges and universities) as well as certain tribal organizations and governments. However, these organizations still must meet the primary gate: they must have an active NIH T32 award and the capacity to support the proposed big data training track.
What institutional capabilities does NIH expect applicants to demonstrate?
NIH expects strong institutional commitment to the expansion, including adequate staffing, facilities, and educational resources. A major expectation is that the institution already has a strong, high-quality biomedical Big Data Science research program with faculty actively engaged in big-data-driven biomedical research across multiple data types.
Why does NIH emphasize having an existing Big Data Science research base?
The FOA anticipates that trainees will gain hands-on, research-based experience by participating in active projects aligned with their interests and career goals. That expectation requires an existing depth of faculty expertise and ongoing big-data-driven biomedical research activities.
Does the Big Data Science track need to be different from current training activities?
Yes. While NIH anticipates that the big data track may complement existing training activities, it should be meaningfully distinct and not simply a minor relabeling of what an institution already does.
What is the funding instrument type?
The Funding Instrument Type is a grant, and the FOA supports competitive supplements (revisions) to active awards rather than standalone new training grants.
How many awards did NIH expect to make, and what was the estimated total funding?
NIH listed an estimated total funding amount of $6,000,000 and anticipated about three awards, indicating a selective competition intended to support a small number of strong program expansions.
Is this opportunity tied to specific diseases or NIH institutes?
The FOA is framed as cross-cutting. It is linked to a wide set of CFDA numbers spanning many NIH institutes and health-related domains (including areas such as human genome research, cancer, mental health, aging, cardiovascular disease, and more). This signals NIH views biomedical big data skills as broadly applicable across many disciplines and disease areas.
What is the timeline for this funding opportunity?
The opportunity was posted and created on April 22, 2014. The closing date was July 28, 2016, and the archive date was August 28, 2016.
Is the FOA still open?
No. Because the closing date was July 28, 2016 and the archive date was August 28, 2016, the announcement is time-limited and is no longer open.
Who sponsored this funding opportunity?
The sponsoring agency is the National Institutes of Health (NIH).
Where were applicants directed to find full details?
The announcement directs readers to the NIH Grants Guide page for the full details of the opportunity.
Who was listed as a contact for technical issues accessing the announcement?
For technical issues accessing the announcement, NIH provided contact information through the NIH Office of Extramural Research (OER) webmaster.
Why did NIH use supplements to active T32 programs instead of creating new programs?
The FOA describes this as a way to accelerate workforce development by leveraging existing training structures. By funding revisions to active T32 programs, NIH could add specialized big data training capacity more rapidly in environments that already had strong training foundations and research depth.
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