Revisions to Add Biomedical Big Data Training to Active Institutional Training Grants (T32)

Funding Agency:
National Institutes of Health

The purpose of this Funding Opportunity Announcement (FOA) is to solicit revisions (competitive supplements) to add a Big Data Science track to currently funded T32 institutional training grants 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 (see definition under Funding Opportunity Description). This proposed training initiative should prepare qualified individuals for careers in developing new technologies and methods that will allow biomedical researchers to maximize the value of the growing volume and complexity of biomedical data.

Applicants are encouraged to utilize all appropriate expertise for the purpose of training Big Data scientists, whether that expertise lies within one or more institutions or within the industrial or public sectors. Applicants are also encouraged to consider whether other BD2K training FOAs, such as RFA-HG-14-004 for new T32 applications and RFA-HG-14-006 for revisions to T15 programs, are a good fit to the proposed training program. A complete list of BD2K FOAs can be found at


  • Letter of Intent Due Date(s): 30 days before the application due date
  • Application Due Date(s): July 28, 2014; July 27, 2015, July 28, 2016, by 5:00 PM local time of applicant organization.

RFA-HG-14-005 Expiration Date July 29, 2016

Agency Website

Eligibility Requirements

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 biomedical 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 biomedical sciences in which participating trainees may gain relevant experiences consistent with their research interests and goals.

The PDs/PIs should be established investigators in the scientific areas relevant to biomedical Big Data Science and capable of providing both administrative and scientific leadership to the development and implementation of the proposed training program.  The PDs/PIs will be expected to monitor and assess the program and submit all documents and reports as required. Since the focus of the training is in the area of developing new approaches and tools for manipulating, analyzing, and interpreting Big Data, the PD/PIs for this type of training program should collectively encompass expertise from all three major scientific areas, including demonstrated research leadership in computer science/informatics, statistics/mathematics, and biomedical science.

The primary PD/PI must ensure that the appropriate faculty work collaboratively and in a sustained manner across scientific disciplines and organizational lines to jointly mentor trainees. Big Data Science is interdisciplinary and includes all three major scientific areas: (1) computer science or informatics; (2) statistics and mathematics; and (3) biomedical sciences. It is anticipated that the training program will have a sufficient number of mentors in all three areas, including biomedical sciences researchers, and will utilize the idea of multiple mentorship.

Funding Type





Curriculum Development
Engineering and Physical Sciences
Medical - Basic Science
Medical - Clinical Science
Medical - Translational

External Deadline

July 28, 2016