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Genetic Epidemiology of Cancer

Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD and surrounding area

Position Description:

Dr. Mitchell Machiela, an investigator in the DCEG Integrative Tumor Epidemiology Branch, is seeking a postdoctoral fellow with interest in conducting integrative analyses on the genetic etiology of cancer. Genetic epidemiology has remarkable potential to improve understanding of cancer etiology by identifying germline genetic variation and acquired somatic mutations associated with cancer risk. Specific areas of Dr. Machiela’s research include:

  • Next generation sequencing studies to identify acquired mutations that could impact cancer risk in special exposure populations (e.g., drug and radiation exposure);
  • Studies characterizing the distribution and determinants of structural mosaic copy number changes in large cancer case/control and cohort studies (~200,000 participants) with existing array genotyping data;
  • Genome-wide association studies in pediatric cancers to identify and functionally map germline variants associated with increased risk (e.g., Ewing sarcoma).

All studies of the genetic etiology of cancer are population-based with extensive data on exposures, genetic variation and phenotypic characterization. The potential candidate will be part of an interdisciplinary team of genetic, bioinformatic and laboratory investigators. The NCI’s Division of Cancer Epidemiology (DCEG) has a long tradition of carrying out large-scale, state-of-the-art population studies and has excellent computing resources for next-generation sequencing and genetic epidemiologic analyses. In addition, DCEG offers extensive career development training through its Office of Education.

For more information about this position, please contact Mitchell Machiela, Sc.D., M.P.H., Earl Stadtman Investigator; Email:


Applicants with a doctoral degree in genetic epidemiology, genetics/genomics, statistical genetics or related field, are encouraged to apply. Experience in analyses of large complex genomic datasets, next-generation sequencing, GWAS, and/or bioinformatic methods is a plus. A successful candidate will have excellent written and verbal communication skills, be self-motivated and able to work in a multidisciplinary team. Salary and benefits are highly competitive and commensurate with experience.

To Apply:

See the Division Fellowship Information for an overview, qualifications, and application details.  Go to  and click on Fellowships & Training. This position is subject to a background investigation.

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