*Applications will be reviewed on a rolling-basis, and this posting will remain open until a qualified candidate is identified.
CDC Office and Location: Two research opportunities are currently available in the Center for Surveillance, Epidemiology and Laboratory Science (CSELS) at the Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia.
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.
Research Project: The project entails collaborating with the Accelerator (XLR) Team on developing models, model transformations, statistical analyses, and ETL data pipelines that will enable the CDC to better analyze, forecast, and predict public health events by leveraging the CDC’s national surveillance data. The selected participant will apply critical thinking skills and creativity to develop new data models of the CDC’s surveillance data in HL7 FHIR and author algorithms to transform data to those FHIR-based data models. Additionally, the participant will demonstrate how statistical analysis can be performed on the FHIR-based data model using both Python and R in modern data analytics platforms such as DataBricks. The participant will collaborate closely with the XLR Team and other CDC FHIR experts to build solutions that meet the differing and sometimes competing needs of internal and external stakeholders of the CDC.
XLR moves fast and has fun. As an R&D group, the team culture and dynamics favor independent action, thought, and experimentation, backed by cross-functional expertise for helping one another work through difficult problems. Team members are encouraged to recommend and even design their own data experiments.
- How national public health surveillance works in the United States
- How to apply HL7 FHIR to a real-world public health surveillance use case
- How HL7 FHIR can be incorporated into modern, cloud-hosted system architectures
- Various data persistence and data processing services on the Azure cloud and how to integrate HL7 FHIR data with these services; examples include the Azure data lake and Azure DataBricks
- Python and/or R programming in the context of both data science and data engineering
- How to develop models, transformations, and analysis using FHIR-formatted national surveillance data
- How to collaboratively solve complex problems as part of a close-knit agile and DevSecOps team that follows hypothesis-driven development
Mentor(s): The mentor for this opportunity is Erik Knudsen (email@example.com). If you have questions about the nature of the research please contact the mentor(s).
Anticipated Appointment Start Date: As soon as a qualified candidate is identified. 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.
Citizenship Requirements: This opportunity is available to U.S. citizens and Lawful Permanent Residents (LPR) only.
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.
Questions: Please visit our Program Website. After reading, if you have additional questions about the application process please email ORISE.CDC.CSELS@orau.org and include the reference code for this opportunity.