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Developing novel statistical methodology for epidemiology and genetics

Investigators in the Biostatistics Branch (BB) develop statistical methods and data resources to strengthen observational studies, intervention trials, and laboratory investigations of cancer.

Research Mission

The mission of the branch is “to contribute to the understanding of cancer etiology and to improve public health through the development and application of quantitative methods.”

BB scientists strive to achieve their goals by:

  1. Collaborating on and selectively leading scientific studies responding to the scientific priorities of DCEG and NCI;
  2. Developing new statistical methodologies for epidemiologic, genomic and laboratory studies;
  3. Developing and distributing tools and analytic software for research use within and outside the DCEG community; and
  4. Providing unique biostatistics training within a scientifically rigorous interdisciplinary cancer research environment.

In DCEG, BB scientists have an ideal environment in which to solve important problems in population-based cancer research. By developing and using cutting-edge statistical methodologies, BB scientists can design and analyze data more effectively, taking full advantage of our rich data sources. BB scientists work as collaborators on all major initiatives within the Division, identifying key questions or problems that require new methods and solutions, both for study design and to make important inferences in DCEG studies. Learn more about BB research areas.

Fellowships

Image of 10 fellows' headshots

Fellows Talk about DCEG

Learn what it means to be a fellow in DCEG.

BB offers opportunities for postdoctoral research in statistical methods for epidemiologic and genetics research. Areas of interest include methods for descriptive epidemiology, risk prediction, screening, environmental epidemiology, dose-response assessment, high-dimensional and longitudinal biomarkers, and population-based inference using sampling methodology.

Other areas include methods for genomic studies including GWAS analysis, somatic mutation analysis, and integrative tumor analysis. Postdoctoral fellows also have an opportunity to collaborate on important epidemiologic studies, many of which include molecular and genetic components.

These opportunities allow recent Ph.D. recipients to build their methodological and collaborative research programs. Strong candidates from statistics and biostatistics doctoral programs who are eligible to work in the U.S. are encouraged to apply. Preference will be given to candidates interested in applied problems, and with superior communication skills.

Meet our current BB fellows and learn about BB research training opportunities.

    sketch of lungs

    Benefits of Reduced Smoking on Lung Cancer

    Fewer cigarettes per day, less time smoked both associated with lower risk.
    photograph of two Black women talking, a doctor and patient

    PRS Improves Risk Prediction for Black Women

    Breast cancer risk prediction improved with addition of a polygenic risk score.
    Image of a two-dimensional polygenic risk score model.

    Branch Profile: Biostatistics

    The Biostatistics Branch is a premier research and training group focused on understanding cancer etiology and improving public health through  the development and application of quantitative methods.

    Collaboration

    Branch investigators are key participants in large, complex, interdisciplinary studies in collaboration with scientists throughout DCEG, across the NCI and NIH, and with investigators and public health officials at other government agencies and academic and research institutions in the U.S. and abroad. 

      Tools and Resources

      BB investigators develop ideas from application-oriented work. New study design and analytic methods are applied to DCEG epidemiological and laboratory studies collaboratively with investigators from other branches to improve what can be extracted from the study data. These methodologies are then distributed to the greater scientific community in the form of statistical and computational tools. Learn more about the tools and resources developed by BB investigators.

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