CDC Epidemiology and Information Science Fellowship

Organization
Centers for Disease Control and Prevention (CDC)
Reference Code
CDC-ID-2021-0053
How to Apply

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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.NCIRD@orau.org. Please include the reference code for this opportunity in your email.

Application Deadline
3/2/2021 3:00:00 PM Eastern Time Zone
Description

*Applications will be reviewed on a rolling-basis.

A fellowship opportunity is available within the Influenza Division (ID) Epidemiology and Prevention Branch of the National Center for Immunization and Respiratory Diseases (NCIRD) at the Centers for Disease Control and Prevention (CDC) located in Atlanta, Georgia. ID provides the scientific and programmatic foundation and leadership for the diagnosis, prevention, and control of influenza domestically and internationally.

The Applied Research and Modeling (ARM) Team, Epidemiology and Prevention Branch, Influenza Division, at the Centers for Disease Control and Prevention is seeking a motivated masters level graduate with a background in epidemiology, biostatistics, or data science. This position will offer a unique opportunity to train with a multi-disciplinary team focusing on innovative ways to gather, analyze, and disseminate public health information. 

The ARM team supports surveillance and research platforms that supplement our understanding of influenza disease burden and severity through data analysis and mathematical modeling. The Team is particularly interested in exploring the potential utility of new and under-used data sources that could allow for better or timelier understanding of the epidemiology and burden of influenza.

Under the guidance of a mentor, the participant will train with researchers on the team on the analysis and visualization of various information sources. The participant will primarily be involved in projects that include: assisting with analysis of various surveillance data sources and special studies in the Branch and use of that data to make routine estimates of influenza disease burden. The participant will also develop an understanding of how analytics and modeling support the response to seasonal and pandemic influenza.  

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.

Qualifications

The qualified candidate should have received a master's degree in one of the relevant fields. Degree must have been received within five years of the appointment start date.

Candidates who are currently pursuing a master's degree with completion by the end of July 2021, please apply to: https://www.zintellect.com/Opportunity/Details/CDC-ID-2021-0053-A

Preferred skills:

  • Coursework or experience with data importation, manipulation, and analysis
  • Experience with SAS and R
Eligibility Requirements
  • Degree: Master's Degree received within the last 60 month(s).
  • Discipline(s):
    • Computer, Information, and Data Sciences (2 )
    • Life Health and Medical Sciences (3 )
    • Mathematics and Statistics (2 )
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