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Discovering the causes of cancer and the means of prevention

Staff Scientist, Integrative Tumor Epidemiology Branch (ITEB)

The Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH) is recruiting a staff scientist in the Integrative Tumor Epidemiology Branch (ITEB).  

Who We Are

DCEG is committed to discovering and understanding the genetic architecture of cancer, including the identification of common and rare loci for cancer risk, exploration of underlying functional mechanisms and the impact of environmental exposures, and use of genetic variants for risk stratification and prevention.  For more information visit the DCEG website.

ITEB conducts large-scale, international epidemiological research on cancer etiology and progression through integrative analyses of risk factors and tissue profiling to inform prevention and clinical strategies. ITEB develops methods to support this cutting-edge research, integrating molecular pathology, somatic and germline genomics, tissue imaging, and epidemiology; trains pre- and postdoctoral fellows in integrative epidemiologic research; and participates in and contributes to national and international organizations and consortia to promote integrative tumor epidemiologic research. All ITEB studies are highly interdisciplinary.

The staff scientist, working under the direction of a senior investigator within ITEB, will have responsibilities for all aspects of two major studies of lung cancer and melanoma and other related projects. Specific duties will include assisting with: management (human subjects’ approvals, contracts and purchasing orders, budgeting and funding management, data coding and cleaning, manipulating and harmonizing data from a variety of sources, specimens tracking, communication with international investigators to monitor study progress, organizing and coordinating meetings; bioinformatics analyses of somatic genomic data (including whole- genome sequencing, methylation analyses and other data types); preparation of reports for presentation or publications; and study design (developing protocols, questionnaires, tools for exposure assessment, specimen and imaging collection procedures). Some international travel is required.


The successful candidate must hold a doctoral degree or equivalent in a relevant discipline (e.g., bioinformatics, computational biology, epidemiology, biostatistics or mathematics).  Experience in applying bioinformatics analyses to high-dimensional molecular epidemiologic data would be an important asset. The study research program also includes biologic specimens, digital pathology and medical imaging data; thus, training in a biologically related field or experience working with laboratory samples and digital imaging data is another important asset. The position requires organizational abilities, attention to detail, initiative, and an aptitude for multi-tasking. The ability to communicate effectively in speech and in writing is essential, as demonstrated in presentations and publications. Salary is commensurate with experience.

How to Apply

Selection for this position will be based solely on merit, with no discrimination for non-merit reasons such as race, color, religion, gender, sexual orientation, national origin, political affiliation, marital status, disability, age, or membership or non-membership in an employee organization. NIH encourages the application and nomination of qualified women, minorities and individuals with disabilities. NIH provides reasonable accommodations to applicants with disabilities. If you require reasonable accommodation during any part of the application and hiring process, please notify us. The decision on granting reasonable accommodation will be made on a case-by-case basis. This position is subject to a background investigation.  
Interested individuals should send a cover letter and curriculum vitae to Ms. Sadie Holmes as detailed below. After initial review, additional materials may be requested from select candidates.

Ms. Sadie Holmes-Lillie
Division of Cancer Epidemiology and Genetics, National Cancer Institute

The closing date for applications is October 13, 2022.