Our research group uses computational modeling to inform and change public health policy in global infectious diseases. We mix fields of epidemiology, engineering, mathematics, and economics to guide pressing policy issues. Past projects have included modeling revision of World Health Organization guidelines for treatment of parasitic worms that affect 1.5 billion of the world’s poorest people, measuring the effectiveness of US government investments in HIV prevention programs, and developing outbreak projections for measles due to vaccine hesitancy. We have published in the top medical journals and been featured in media (New York Times, BBC, NPR). Our track record includes many projects in infectious disease policy that have translated into policy changes and practice, including in the fields of neglected tropical disease and HIV. Many of the investigators work closely with the World Health Organization (Geneva) to ensure our research translates to improve human health.

Full time staff research position
We are recruiting for one full time position who is interested in working on computational public health research related to infectious diseases. The project would focus on developing computational models to improve infectious disease surveillance and guide public health decisions. The position requires the following:
• PhD in engineering, statistics, computer science, epidemiology or related field. Qualified applicants with Bachelor's or Masters degree may apply.
• Strong programming skills in at least one of the following languages (R, MATLAB, Python).
• Strong quantitative skills, including decision science, microsimulation, intermediate biostatistics, and basic mathematics (e.g. differential equations).
• Knowledge of epidemiology and population health measurement.
• Ability to work independently and execute research projects with minimal supervision.
• Excellent communication skills (e.g. data visualization, writing).
• Commitment of 2 years.

You will work under the supervision of Dr. Nathan Lo (Stanford MD/PhD) and other members of the laboratory. This position will be funded, and you will also be credited academically for your contribution. If you are interested, please contact us with your CV and cover letter (Nathan.Lo@stanford.edu).