CDC Data Analysis Fellowship
A complete application consists of:
- An application
- Transcripts – Click here for detailed information about acceptable transcripts
- A current resume/CV, including academic history, employment history, relevant experiences, and publication list
- One educational or professional recommendation. Your application will be considered incomplete, and will not be reviewed until one recommendation is submitted.
All documents must be in English or include an official English translation.
If you have questions, send an email to ORISE.CDC.NCCDPHP@orau.org. Please include the reference code for this opportunity in your email.
A research opportunity is currently available in the Epidemiology and Statistics Branch (ESB), Division of Diabetes Translation (DDT) within the National Chronic Disease Prevention and Health Promotion (NCCDPHP) at the Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia.
In this project, the selected candidate will receive the following training and learning experience provided by ESB economic team: (1) how to synthesize and translate empirical evidence on cost-effectiveness of interventions for the prevention and control of diabetes; (2) how to conduct studies of health care utilization and costs associated with diabetes and related complications using varied data sets, including healthcare administrative data from the Centers for Medicare and Medicaid Services (CMS) accessed through the CMS Virtual Research Data Center, National Health and Nutrition Examination Survey, National Health Interview Survey, and Medical Expenditure Panel Survey; and linked data sets; (3) how to use diabetes computer simulation models to project the long-term health and economic consequences of implementing strategies/interventions/policies for preventing and managing diabetes, compared with no intervention or status quo. This includes training in conducting data analysis to generate the characteristics of the simulation population and running the simulation models for epidemiological and cost-effectiveness analysis.
Under the guidance of a mentor, the participant will receive training in how to perform the following:
- Conduct literature search, data analysis, statistical programming, and simulation modeling methodological research activities in support of ESB economic team agenda
- Collaborate with ESB economic team members to plan, develop, and complete a research project relating to studies of health care utilization and costs associated with diabetes and related complications and epidemiological and cost-effectiveness analysis
- Prepare tables and figures, and reports from the various projects for publications
Anticipated Appointment Start Date: August 1, 2019
This program, administered by ORAU through its contract with the U.S. Department of Energy to manage the Oak Ridge Institute for Science and Education, was established through an interagency agreement between DOE and CDC. The initial appointment can be up to one year, but may be renewed upon recommendation of CDC contingent on the availability of funds. The participant will receive a monthly stipend commensurate with educational level and experience. Proof of health insurance is required for participation in this program. The appointment is full-time at CDC in the Atlanta, Georgia, area. Participants do not become employees of CDC, DOE or the program administrator, and there are no employment-related benefits.
The qualified candidate should have received a master's or doctoral degree in one of the relevant fields, or be currently pursuing one of the degrees and will reach completion by the end of May 2019. Degree must have been received within five years of the appointment start date.
Preferred skills/experience:
- Strong quantitative skills
- Experience using large data sets such as insurance claim or National Survey data
- Experience using statistical software such as SAS, Stata
- Scientific writing
- Degree: Master's Degree or Doctoral Degree received within the last 60 months or anticipated to be received by 5/31/2019 12:00:00 AM.
- Discipline(s):
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