The National Cancer Institute (NCI) has openings for several positions within the Surveillance Research Program (SRP), Division of Cancer Control and Population Sciences (DCCPS). SRP sets the direction for statistical research, modeling, reporting and interpretation of cancer epidemiological surveillance data in order to measure progress in reducing the US cancer burden. SRP manages the Surveillance, Epidemiology, and End Results (SEER) Program, a comprehensive population-based cancer reporting system. SRP provides leadership in developing statistical methodologies appropriate for analyzing trends and for evaluating the impact of cancer control interventions as well as geographic, socioeconomic, behavioral, genetic, and health care delivery factors on the cancer burden. Statistical and mathematical modeling increases the utility of data for assessing progress in cancer control. SRP funds a broad portfolio of statistical methods grants in areas relevant to the substantive research areas across DCCPS.
SRP is expanding the scope and utility of the SEER data through linkages with other key data sources, and new, exciting opportunities are available. Areas of interest for the program include:
- Harmonization, enhancement, and validation of novel sources of data and variables to expand the utility of cancer surveillance data. Examples include:
- Multiple Imputation for missing data (e.g. biomarkers)
- Methods to examine the biases and population representativeness of new linked cohorts
- Linkage assessment
- Measures of data quality
- Analysis of large and complex data sets. Population data in cancer surveillance have a complex structure that includes time and space correlations, multilevel structure, and missing data. Methods include the use of complex survey data, especially small area estimation.
- Evaluation and reporting of cancer progress measures and indicators spanning the cancer continuum. These include analyses of the SEER-Medicare data and other data sources, to evaluate and report on patterns of care, health disparities and other measures.
- New cancer progress measures and methods for the reporting and interpretation of national cancer statistics. Examples are survival cure models, change-point models, back-calculation methods, and competing risk modeling.
- Scientific management and collaborative opportunities with the Cancer Intervention and Surveillance Modeling Network (CISNET). This consortium uses simulation modeling and decision analysis to improve our understanding of the impact of cancer control interventions in prevention, screening, and treatment on population trends in incidence and mortality. These models have been used to guide public health research and priorities, and aid in the development of optimal cancer control strategies, including screening guidelines for the US Preventive Services Task Force and other guideline setting organizations.
- Demographic methods related to estimating population-based rates, including issues of differential privacy in population census data, and the estimation of rates using population estimates from the American Community Survey.
Each position includes responsibility for initiating and managing collaborative analyses with scientists from NCI and other institutes, agencies and academic centers and managing a portfolio of grants and contracts. Applicants with doctoral or master’s degrees in statistics, biostatistics or a related area with experience related to the analysis and interpretation of health statistics are being sought. Excellent communication and interpersonal skills are essential for working in this interdisciplinary setting with many collaborators.
The location is Rockville, Maryland, close to Washington D.C. This position is subject to a background investigation and U.S. citizenship is required for federal positions. Excellent benefits. The National Cancer Institute is an Equal Opportunity Employer (Equal Employment Opportunity (EEO) for federal employees & job applicants).
Please send a CV and a letter describing your background and interests, by email, to Annie Noone.
Please visit our Web pages:
The Surveillance, Epidemiology, and End Results (SEER) Program
Surveillance Research Program (SRP)