Intern-Software Test Engineer

Location: Bellevue, WA, USA

Ref: is20190222

Date Published: February 22, 2019

The Institute for Disease Modeling (IDM), part of Intellectual Ventures’ Global Good program, is committed to improving and saving lives in developing countries using quantitative analysis. The IDM team is composed of research scientists and software professionals who create advanced models of disease transmission, develop computational tools to inform global disease eradication policy, conduct analysis of epidemiologically- and policy-relevant data, and identify critical knowledge gaps. IDM is a highly dynamic organization with a work environment that is defined by innovation and collaboration. As part of our work, we routinely collaborate with groups at the World Health Organization, the Center for Disease Control, PATH, the Bill and Melinda Gates Foundation, ministries of health in the developing world, as well as universities and research institutes.

IDM's Computational Model Test Team has automated statistical tests of our infectious disease model that run with our regular builds of our modeling software. Currently, these tests are executed through our regression testing scripts. This project is to get these tests adapted to run through the same simulation management software used by our Infectious Disease modeling teams.


  • Refactor existing Scientific Feature Tests (SFTs) of the Disease Transmission Kernel (DTK) to use the param_overrides features of the DTK regression harness (, and become familiar with ( functionality
  • Building upon previous refactor, refactor existing python tool (dtk-tools) based tests of DTK features to consume parameter override features and become familiar with DTK tools functionality
  • Building upon both previous refactors, create new tests of an existing DTK model to allow statistical validation of stochastic model features that can be used as examples for modeling scientists

Key Qualifications and Required Skills:

  • Experience in software development in python
  • Use of distributed source control (GitHub preferred)
  • Use of defect tracking systems (GitHub issues, JIRA tickets, or equivalent)
  • Use of statistical software (Python Pandas preferred, R or other statistical libraries acceptable)
  • Background in a natural science (Physics, Chemistry, Biology, Astronomy, etc) preferred

Joining our group provides unique opportunities to interact with global-health policymakers, to collaborate with world-class research laboratories and non-profit organizations, and to contribute to global and national disease control strategies.

We are an equal opportunity employer