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Research Scientist - Measles and Vaccine-Preventable Diseases

Bellevue, Wa, Washington, United States

Ref#: 3557

Date published: 21-Aug-2018

As part of Intellectual Ventures' Global Good initiative, the Institute for Disease Modeling’s (IDM) mission is to guide global efforts towards the eradication and control of infectious disease through the use and promotion of 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.

We seek a full-time Research Scientist to work as part of the IDM global development research team to collaborate on the development, refinement, and application of sophisticated models of vaccine-preventable infectious diseases for epidemiological research and eradication-campaign planning, focusing primarily on immediate applications to measles. The scientific responsibilities of this role will include a combination of: analyzing existing data on immunization and disease incidence; utilizing and refining IDM’s existing measles models; identifying promising new modeling approaches in the literature and implementing them; executing model-based experiments to investigate pressing questions in disease control and eradication policy; visualizing complex data and simulation outputs; and clarifying key dependencies and uncertainties in their results. The scientist will also collaborate with IDM team members to integrate their work into a robust data processing and modeling framework, publish the results of their analyses, and present their work to key stakeholders in global health.

Joining our group provides unique opportunities to interact with global-health policymakers, to collaborate with world-class researchers and non-profit organizations, and to contribute to more effective burden reduction and disease eradication strategies.

  • Reviews scientific literature to determine the state of knowledge underlying disease control strategies and to identify which aspects of biology, demography, geography, and climate are relevant to modeling alternative strategies.
  • Builds new features for existing disease models; designs and implements new modeling methods.
  • Works closely with the modelers, programmers, and statisticians on the team to refine disease models and use them to conduct sensitivity analyses, explore tradeoffs among possible interventions, and optimize burden reduction and eradication plans for time, cost, or other factors.
  • Gathers, processes, and organizes necessary input data for the models.  These data may take the form of surveys, maps or GPS coordinates, administrative data, hospital records, etc.
  • Writes flexible, reusable software code to analyze raw model outputs and generate insightful summaries and visualizations of the results. 
  • Prepares research articles and conference presentations to communicate their results to the scientific community and to global health policy makers.
  • Write summaries of his/her results to be used in policy recommendations, white papers, and scientific publications
Key Qualifications and Required Skills:
  • PhD in a quantitative field (e.g. Physics, Applied Mathematics, Statistics, Computational Biology)
  • Proficiency in at least one data-analysis or scripting language (e.g. MATLAB, python, R)
  • Knowledge of numerical analysis, dynamical systems, stochastic processes, or biostatistics. 
  • Familiarity with principles and techniques of computational modeling
  • Ability to read and write research articles.
  • Attention to detail and high standard for quality of work product
  • Must be a clear and effective communicator
  • Work extended hours to meet a deadline, and a demonstrated ability to work productively as part of a team.
  • Experience analyzing large (TB-scale) datasets is a plus.
  • Knowledge of issues of public health in developing world settings is a plus
  • Experience working with a software development team or on collaborative software projects is a plus
  • Must be highly self-motivated and results-oriented
We are an equal opportunity employer
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