The Radiation Epidemiology (REB) and Biostatistics Branches (BB) of the Division of Cancer Epidemiology and Genetics at the National Cancer Institute/National Institutes of Health/Department of Health and Human Services seek qualified applicants for post-doctoral fellowships for interdisciplinary research on statistical issues in studying the role of radiation in cancer etiology.  The Division of Cancer Epidemiology and Genetics (DCEG) of the National Cancer Institute conducts a national and international program of population- and family-based studies to elucidate the environmental and genetic determinants of cancer. REB conducts research to identify, understand, and quantify the risks of cancer in populations exposed to medical occupational, or environmental radiations, and to advance understanding of radiation carcinogenesis. BB statisticians collaborate across wide variety of studies in DCEG and develop cutting-edge statistical methods in diverse areas such as machine learning, measurement error, study design, the analysis of correlated data, statistical genetics, genomics, and risk–prediction.

The successful candidate for this position will be jointly mentored by investigators from REB and BB. Depending on one’s interest, projects may include the collaboration on radiation epidemiologic studies that require assessment of doses in studies as a prelude to risk evaluation and non-standard modeling of the dose-response relationship between radiation and cancer risk. There is particular interest in application of machine learning methods to these areas. The candidate will also be given flexibility to pursue research in broader statistical areas, such as machine learning methods and measurement error that have applications beyond radiation epidemiologic studies.

The fellow will have opportunity to work together with a highly talented team of researchers with experience in radiation, statistics, epidemiology, dosimetry, and genomics. Access to data from a large variety of one-of-a- kind cohort studies (e.g., REB’s signature cohort studies of cancer risks in children who underwent CT scans and a case-control study of children exposed to background radiation in the UK) would provide an excellent opportunity for identifying important problems, testing and validating the statistical methods and eventually applying them for improved analysis and interpretation of substantive studies.  The fellow will have access to high performance computing facilities.