Funding Opportunities

Office of Behavioral and Social Sciences Research (OBSSR) National Institute on Alcohol Abuse and Alcoholism (NIAAA)Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institute on Drug Abuse (NIDA)National Institute of Mental Health (NIMH) National Institute of Nursing Research (NINR) National Library of Medicine (NLM)

The National Institutes of Health (NIH) Office of Behavioral and Social Sciences Research (OBSSR) and participating NIH Institutes and Centers (ICs) intend to issue a Funding Opportunity Announcement (FOA) to solicit applications for new behavioral and social sciences research (BSSR) predoctoral training programs that focus on innovative computational and/or data science analytic approaches and their incorporation into training for the future BSSR health research workforce.   This Notice is being provided to allow potential applicants sufficient time to develop meaningful cross-disciplinary collaborations and responsive training programs.   This FOA will utilize the T32 activity code.   The FOA is expected to be published in October 2018 with an anticipated application due date in May 2019.

Recent advances in medical informatics, electronic health records, big data analytics, mobile and wearable technologies, social media and web generated data, geospatial data, administrative data, and new methods to link data have laid the groundwork for a rich biomedical, behavioral, and social research data environment. The voluminous data environment resulting from diverse data sources will require complex analytical skills to derive rigorous scientific knowledge. The vision of the Office of Behavioral and Social Sciences Research (OBSSR) Advanced Data Analytics for Behavioral and Social Sciences Research (BSSR) Training Program is to support the development of a pilot program cohort of specialized BSSR predoctoral candidates pursuing careers in health-related research who will possess advanced competencies in data science analytics.

 Big data in the behavioral and social sciences tends to come from mixed sources (e.g., social media, unstructured text, digital sensors or wearables, administrative databases, high-density census population datasets with geographic detail), they are often generated dynamically over time and not necessarily designed to produce valid or reliable data for scientific analysis. Applying advanced analytic approaches to these kinds of data provides opportunities to transform the spatiotemporal analysis of demographics, behaviors, social interactions, and economics as they relate to health outcomes. Working with disparate social data streams requires careful attention to structuring, harmonizing and extracting meaningful features from the data, which in turn, requires advanced computational and data science statistical approaches. In addition, BSSR data are becoming increasingly interdisciplinary as they are combined and merged with biomedical, genetic, geospatial, and administrative data. Successful collection and rigorous analysis of complex behavioral and social science health data will require solid scientific critical thinking skills, new cross-disciplinary collaborations, new research methods, and new computational tools and data science approaches such as data mining, pattern recognition, machine learning, computational modeling, causal inference, and a keen awareness of the continuously emerging data methods, challenges, and opportunities.

This funding opportunity announcement will require applicants to assemble an interdisciplinary team of scientific mentors to design and direct training programs. Applications must include mentors from relevant behavioral and social sciences research (BSSR) disciplines such as psychology, sociology, or economics, as well as experts in computational or data science analysis approaches from relevant disciplines such as engineering, computer science, applied mathematics, statistics, or physics departments. Programs should provide predoctoral level instruction and practical experience in advanced data analytics relevant to research in domains of health best suited for BSSR inquiry. The foundational training for these BSSR predoctoral programs should include coursework and training experiences in academia or industry, a multidisciplinary team approach, collaborative research opportunities, and should ensure adequate mentorship in computational methods with an emphasis on principles and practices that promote reproducibility of results. It is expected that trainees will acquire core knowledge in three overarching relevant areas in: (1) computer science/informatics, (2) statistics/mathematics, and (3) behavioral and social sciences research in a chosen health domain relevant to the NIH institutes and centers participating in this program announcement. The training should include aspects of computer science/informatics and statistics/mathematics that are directly relevant to behavioral and social sciences research in health.

Estimated Total Funding $2,000,000 Expected Number of Awards 8 Estimated Award Ceiling $300,000 Primary CFDA Numbers TBD

Public/State Controlled Institution of Higher Education Private Institution of Higher Education Nonprofit with 501(c)(3) IRS Status (Other than Institution of Higher Education) Nonprofit without 501(c)(3) IRS Status (Other than Institution of Higher Education) State Government Indian/Native American Tribal Government (Federally Recognized) County governments City or township governments Special district governments Indian/Native American Tribally Designated Organization (Native American tribal organizations (other than Federally recognized tribal governments) U.S. Territory or Possession Indian/Native American Tribal Government (Other than Federally Recognized)

Applications are not being solicited at this time.