Biostatistics Training Grant Program

Contact: Dr. Kenneth Gibbs -- 301-594-3901

The purpose of these programs is to provide support for predoctoral training in biostatistical theory and evolving methodologies related to basic biomedical research including, but not limited to, bioinformatics, genetics, molecular biology, cellular processes and physiology, as well as epidemiological, clinical and behavioral studies. The goal is to ensure that a workforce of biostatisticians with a deep understanding of statistical theory and new methodologies is available to assume leadership roles related to the Nation’s biomedical, clinical and behavioral research needs. Implementation will depend on the integration of biostatistics and basic biological sciences to create effective interdisciplinary training grant programs. The aim is to provide students with strong quantitative talents to pursue a wide range of opportunities in biostatistics research.

Applicants for a predoctoral institutional training grant in biostatistics need to describe an interdisciplinary program that is built on a strong foundation in statistical theory and methodology and that provides a clear understanding of basic biological research, including bioinformatics, computational biology and the relationship of these scientific domains to epidemiological, clinical and behavioral research. Applications should address the challenges of melding two disparate cultures, statistics and biology, at both the faculty and student levels. These challenges include:

  • Creating a collaborative infrastructure for training faculty: To develop a vital collaborative infrastructure that provides interdisciplinary training, faculty must be recruited from more than one department. Evidence for this infrastructure could include collaborative research projects, co-authored publications, joint service on dissertation committees, collaborative teaching and regular interactions in journal clubs and seminar series.
  • Training of graduate students from diverse scientific backgrounds: The application should address at least two scenarios for student success, one involving students coming from a biological background and the other involving students coming from a quantitative or computational science background.
  • Degree requirements: While it is recognized that biostatistics depends on a theoretical formalism that requires an essential core of didactic courses, this requirement must be balanced with training in other disciplines. Applicants must identify the key ideas and skills that are essential to multidisciplinary training in biostatistics and monitor the impact of core requirements on time to degree.