Work on a highly collaborative project that includes partners in industry, academia, and government. Methods developed over the course of this project will be applied to inform public health interventions to control infectious disease outbreaks such as cholera, Ebola, Zika, and SARS-CoV-2. The position will provide the opportunity to develop innovative approaches to forecasting and causal inference and apply those methods to solve real-world problems in outbreak response.

Educational Requirements:
PhD in epidemiology, biostatistics, computational biology, public health, or a related field

Required Qualifications and Experience:
Some familiarity with methods in infectious disease dynamics, causal inference, or both.
Experience programming in statistical or general programming languages
Highly motivated, organized, and comfortable working with other investigators to meet deadlines

Preferred Qualifications and Experience:
The ideal candidate would have experience writing packages in R and/or Python and familiarity with unit and integration testing and version control systems like Git.
Experience in the management of large-scale research, scientific, medical, or academic projects