Research Intern - Computational Science

Location: Bellevue, WA, USA

Reference: in20200122-4

Date Published: January 22, 2020

The Institute for Disease Modeling produces sophisticated computational models for various epidemiological processes, such as malaria, HIV, polio, typhoid, measles and more. By leveraging super-computing platforms to simulate a variety of existing and novel interventions thousands of times, we can determine what will work before recommending policy changes. However, these models are challenging to use. They are difficult to fit to historical country contexts, and hard to optimize for impact or cost effectiveness.

Ensuring women have access to safe, reliable, and affordable family planning methods is one of the most impactful public health interventions there is. However, relatively little quantitative modeling has been done to determine which people and places would benefit most from different types of family planning interventions. This project will use the latest available data to inform a mathematical model of family planning interventions and their impacts in Nigeria. By determining the expected costs and impacts of different intervention scenarios, we aim to provide policy advice to help maximize both child and maternal health.


  • Read academic literature on methods for stochastic models.
  • Implement one or more algorithms.
  • Develop tests that algorithms are working as expected.
  • Support research applications of advanced methods.
  • Improve workflow efficiency.


  • Familiar with classical optimization theory.
  • Ability to read and write academic papers.
  • Basic knowledge of computational statistics (e.g. Monte Carlo).
  • Proficiency in python programming is required.
  • Works well in a team setting.
  • GitHub experience a plus.
  • GPU programming a plus.


We are an equal opportunity employer