CDC Epidemiology Fellowship with focus on Spatial Analysis

CDC Epidemiology Fellowship with focus on Spatial Analysis

For full description and details to apply:  Zintellect – Climb Higher

Research Project: Under the guidance of a mentor, the selected participant will have the opportunity to train and gain experience in advanced spatiotemporal studies with a focus on heart disease and stroke.  Projects will address health equity issues, including identifying and studying differences by social and economic context, urban-rural status, and racial/ethnic group.  

Learning Objectives

Learning to create, update, analyze and manage very large datasets

Training and participating in advanced spatial and/or spatiotemporal analyses of heart disease and stroke morbidity, mortality and risk factors using Bayesian and frequentist approaches

Gaining experience writing manuscripts for submission to peer-reviewed journals and government reports

Producing data visualizations of spatiotemporal data

Conducting literature reviews

Presenting the results to internal and external audiences, including professional meetings and/or conferences

Other related activities as discussed with mentor that further the science base regarding conducting small area analyses and advancing CDC’s research related to cardiovascular risk factors and outcomes.

Anticipated Appointment Start Date: April 2022. Start date is flexible.

Level of Participation: The appointment is full-time.

Qualifications: The qualified candidate should have received a master’s or doctoral degree in one of the relevant fields (e.g. public health, epidemiology, biostatistics, or similar field) or be currently pursuing one of the degrees to be received by the end of May 2022. Degree must have been received within the past five years.

Preferred skills:

Experience analyzing spatial and/or spatiotemporal data

Experience with studies that address social determinants of health and/or health inequities

Knowledge/Awareness of Bayesian statistical methods

Experience using statistical software, such as SAS or R, for data analysis

Experience using ArcGIS or other mapping software packages

Strong written and oral communication skills

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