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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.

*Applications will be reviewed on a rolling-basis.

CDC Office and Location: A research opportunity is currently available in the Office of the Branch Chief of the Data Analytics Branch (DAB), Divisions of Injury Prevention (DIP), National Center for Injury Prevention and Control (NCIPC) at the Centers for Disease Control and Prevention (CDC) located in Atlanta, GA. The option for majority remote work will be considered.

The Centers for Disease Control and Prevention (CDC) is one of the major operation components of the Department of Health and Human Services. CDC works to protect America from health, safety and security threats, both foreign and in the U.S. Whether diseases start at home or abroad, are chronic or acute, curable or preventable, human error or deliberate attack, CDC fights disease and supports communities and citizens to do the same.

DAB is comprised of four separate teams: The Economics Team, the Statistics Team, the Programming team and the Data Science Team. NCIPC's mission is to prevent violence and injuries through science and action. DIP leads CDC's efforts to reduce unintentional injuries and self-directed harm. DAB conducts methodological research and data analysis, addresses existing data issues and new data challenges (big, complex, non-traditional data) and develops and disseminates data, tools and applications.

Research Project: This appointment will provide an excellent training opportunity for the selected fellow to gain experience in epidemiology and data science in a public health setting focused on injury-related topics, such as suicide, drug overdose, and violence. The participant will be mentored by an epidemiologist knowledgeable in data visualization and will receive additional mentorship from data scientists. Additionally, the fellow will have the opportunity to interact with programmers, economists and statisticians on injury-related projects. 

Learning Objectives: Under the guidance of a mentor, the participant will receive practical training by participating in a variety of projects utilizing different epidemiological and data science methods, including: 

• 1. Data Science – The fellow will receive training in conducting data science projects within the NCIPC. The fellow will assist the Data Science Team with a number of different projects including projects focused on Natural Language Processing and use of machine learning.  Examples of past projects include using machine learning models to identify opioid overdose visits in emergency department visit data and identifying alcohol-related emergency department visits. Ongoing projects includes creating an R Shiny app to facilitate text searches of emergency department visit data.
• 2. Data Visualization – The fellow will receive training on data visualization.  An example of a recent project is creating a user interface that will automatically combine data from various injury databases to generate user-friendly infographics. 
• 3. Mentorship and Training – The fellow will receive mentorship and training for professional development. Relevant training to advance skills in epidemiology and data science will be provided under direct mentorship of the Branch-level epidemiologist (primary mentor) and members of the Data Science Team. Data science training and additional public health courses will be accessible through CDC.
• 4. Summary Reports, Presentations and Publications – The fellow will have the opportunity to present internally to NCIPC colleagues and externally at meetings and conferences.  The fellow will receive support to develop research ideas, analyze data and write manuscript(s) for submission to peer-reviewed journals.

Mentor(s): The mentor(s) for this opportunity is Livia Navon (len8@cdc.gov). If you have questions about the nature of the research please contact the mentor(s).

Anticipated Appointment Start Date: September 6, 2022.  Start date is flexible and will depend on a variety of factors.

Appointment Length: The appointment will initially be for one year, but may be renewed upon recommendation of CDC and is contingent on the availability of funds.

Level of Participation: The appointment is full-time.

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience. A travel/training allowance may also be provided based on the discretion of the mentor and the CDC program. 

Citizenship Requirements: This opportunity is available to U.S. citizens and Lawful Permanent Residents (LPR).

ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and CDC. Participants do not become employees of CDC, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.

The successful applicant(s) will be required to comply with Environmental, Safety and Health (ES&H) requirements of the hosting facility, including but not limited to, COVID-19 requirements (e.g. facial covering, physical distancing, testing, vaccination).

Questions: Please visit our Program Website. After reading, if you have additional questions about the application process please email ORISE.CDC.NCIPC@orau.org and include the reference code for this opportunity.

The qualified candidate should have received a master's degree in one of the relevant fields (Public Health, Epidemiology, Statistics, Computer Science, Data Science), or be currently pursuing the degree with completion by September 6, 2022. Degree must have been received within the last five years.

• Experience and knowledge of statistics
• Experience with data analysis 
• Experience and knowledge of data science and approaches to data analysis
• Training in epidemiology 
• Excellent written and verbal communication skills 

• Citizenship: LPR or U.S. Citizen
• Degree: Master's Degree received within the last 60 months or anticipated to be received by 9/6/2022 11:59:00 PM.
• Overall GPA: 3.50
• Discipline(s):
  • Computer, Information, and Data Sciences (5 )
  • Life Health and Medical Sciences (5 )
  • Mathematics and Statistics (5 )
  • Social and Behavioral Sciences (3 )