BD2K Mentored Career Development Award in Biomedical Big Data Science for Clinicians and Doctorally Prepared Scientists (K01) | Apply Online

Frequently Asked Questions (FAQs)

What is the BD2K Mentored Career Development Award (K01) described here?

It is a discretionary NIH grant mechanism under the NIH Big Data to Knowledge (BD2K) initiative. The specific opportunity is titled "BD2K Mentored Career Development Award in Biomedical Big Data Science for Clinicians and Doctorally Prepared Scientists (K01)" and is designed to develop the next generation of independent investigators in biomedical Big Data science through structured, mentored career development.

What is the Funding Opportunity Number (FON) for this grant?

The Funding Opportunity Number listed is RFA ES 16 002.

Who is the sponsoring agency for this opportunity?

The sponsoring agency is the U.S. Department of Health and Human Services, National Institutes of Health (HHS-NIH11).

What is the main purpose of this K01 opportunity?

The main purpose is to fund a person’s transition into independence in biomedical Big Data science. The emphasis is not simply on funding a standalone research project, but on supporting a candidate through a mentored research plan paired with a deliberate career development plan so they can become competitive for later independent research funding.

Is this opportunity more focused on funding research or funding career development?

Based on the description provided, it is primarily a mentored career development pathway. Research is a core component, but it is intentionally structured around training, mentorship, and skill development that leads toward independence.

What types of applicants is this award intended for at the individual level?

The opportunity is aimed at clinicians and doctorally prepared scientists (PhD-level or equivalent), with the goal of helping promising candidates gain advanced training and hands-on experience in modern, data-intensive biomedical research.

Why does the program emphasize multidisciplinary teamwork?

The program highlights that biomedical Big Data problems often require collaboration across multiple fields, including medicine, biology, computer science, statistics, informatics, engineering, and related disciplines. It targets researchers who can contribute individually while also functioning effectively within multidisciplinary teams.

What kinds of research or development activities fit within "biomedical Big Data science" for this award?

The opportunity emphasizes developing new technologies, methods, and tools that make large-scale biomedical data more usable and informative for both basic and clinical research. Examples described include developing or improving computational methods, algorithms, analytical workflows, data integration approaches, data management strategies, or other toolsets that help extract reliable knowledge from complex, high-volume, high-velocity, or high-variety biomedical datasets.

What is the role of mentorship in this K01 award?

The award is structured around close guidance from one or more experienced mentors and a training environment that supports the candidate’s growth. The mentored period is intended to help awardees fill critical skill gaps, publish, establish a recognizable research niche, and increase competitiveness for later independent funding.

What outcomes does NIH appear to expect from awardees during the mentored period?

The description points to several expected outcomes: gaining advanced Big Data skills, producing meaningful research outputs, publishing, developing an identifiable niche in biomedical Big Data science, demonstrating increasing independence over time, and becoming competitive for subsequent independent research funding.

What makes a strong application, based on the information provided?

The strongest applications are described as those that align a candidate’s clinical or doctoral background with a clear plan to deepen expertise in Big Data methodologies while producing research outputs that show a trajectory toward independence. In other words, the application should connect the candidate’s starting point, their skill gaps, the proposed mentored training, and the planned research into a coherent pathway to independence.

Which organizations are eligible to apply?

Organizational eligibility is described as broad and includes U.S.-based entities such as state, county, and city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments and other tribal organizations; public housing authorities/Indian housing authorities; nonprofit organizations with or without 501(c)(3) status (with the noted caveat "as long as they are not institutions of higher education when specified"); for-profit organizations other than small businesses; small businesses; and other organizations as allowed by the additional eligibility language in the full announcement.

Does the posting specify an award ceiling or the expected number of awards?

No. The source data described does not provide an award ceiling or the expected number of awards, suggesting those details may have been included elsewhere in the full funding opportunity announcement or left flexible based on available funds and application quality.

What are the key dates listed for this opportunity?

The creation and posted date is May 4, 2016. The original closing date and the current closing date are both listed as August 1, 2016.

What does it mean that this is a discretionary NIH grant mechanism?

The posting characterizes it as discretionary, meaning it is a grant mechanism offered by NIH to advance a particular programmatic goal (here, building capacity in biomedical Big Data science). The description provided does not add further administrative detail beyond that characterization.

How does this opportunity relate to the NIH BD2K initiative?

It sits under the broader NIH Big Data to Knowledge (BD2K) initiative and is positioned as part of NIH’s effort to strengthen the workforce and capabilities needed for data-intensive biomedical research.

What is the overall "big picture" way to understand this opportunity?

The opportunity is best understood as a career acceleration pathway for clinicians and PhD-level scientists. It supports mentored training and research in biomedical Big Data science with the explicit goal of producing independent investigators who can create and apply robust data-driven methods and tools that improve discovery and translation in basic and clinical research settings.

Are CFDA numbers associated with this opportunity, and what does that imply?

Yes. The opportunity is associated with a wide set of CFDA numbers, which is described as reflecting participation or relevance across multiple NIH institutes and centers and signaling that Big Data science is cross-cutting across many biomedical domains.