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Discovering the causes of cancer and the means of prevention

Biostatistics Opportunities with Specific Investigators

Current Training Opportunity(s)

  • Training on integrative analysis of multi-platform high-dimensional cancer genomics data with epidemiology and clinical outcomes Dr. Bin Zhu


    Dr. Zhu is seeking a Postdoctoral Fellow for a two-year appointment with possible extension to work on integrative analysis of multi-platform high-dimensional cancer genomics data with epidemiology and clinical outcomes. The position will be focused on development and application of statistical methods in two major areas: 1) identification of regulatory components that “drive” cancer development; 2) integration of clinical and multi-platform molecular data for survival prediction in cancer patients. Candidate will work with and potentially other principle investigators of Biostatistics Branch.


    The candidate will be able to expand his/her analytic and scientific skills that are essential for cancer genome research and precision medicine in oncology

    Position Qualifications

    Candidate will have a Ph.D. in statistics, biostatistics, bioinformatics, computer science or a related field, and should have strong knowledge of statistical theory and excellent skills in computer programming.


    Applicants should send a CV, a short research statement, and names of three referees to ( . Review of applications will begin immediately, and continue until the position is filled.


  • Training in Applied Statistics and Quantitative Epidemiology with Dr. Hormuzd Katki
    Overview: is looking for a postdoctoral fellow interested in developing statistical methods for epidemiology or conducting sophisticated quantitative epidemiologic analyses. Possible areas for developing statistical methods include evaluating risk models, developing dynamic risk models, analyzing massive administrative databases, or applying sampling theory to epidemiology. Possible areas of quantitative epidemiologic analysis include developing risk calculations using a variety of data sources for clinical use in cervical cancer screening and lung cancer screening, evaluating the potential impact of hypothetical screening programs, and quantifying the benefits of smoking cessation. The emphasis of the research will be on applications addressing important public health and clinical questions with primary data. In addition to strong quantitative and computational skills, this position requires either knowledge of methods for epidemiologic studies or solid statistical training. For more details on the opportunity, please contact Dr. Katki (

See the Division Fellowship Information page for an overview, qualifications, and application details.

DHHS and NIH are Equal Opportunity Employers.