We're always seeking extraordinary and creative individuals to tackle the challenging research problems in global health. The Institute for Disease Modeling (IDM) is a highly dynamic organization with a work environment that is defined by innovation and collaboration. Our research and software teams are made up of a diverse and talented group of individuals attacking the complex problems found within global health to improve the world we live in. As part of Intellectual Ventures Global Good initiative, IDM is committed to improving and saving lives in developing countries through the use of quantitative analysis.
We seek a full-time Research Scientist to join IDM’s Applied Math team, which aims to develop algorithms and workflows that increase the usability, capability, and efficiency of the end-to-end modeling process. The Research Scientist will conduct novel and translational research to support the use of data and models in making better decisions regarding health and development. In addition to algorithm development, the scientist will apply and refine these methods in partnership with programmatic teams within IDM and beyond. Successful applicants will command a deep and diverse technical knowledge of applied mathematics, computer science, and statistics.
IDM is seeking a Software Development Engineer in Test (SDET) to bring their passion for software quality to bear on the challenges of infectious disease eradication. The SDET will work closely with scientists and software developers to manually test new features and develop automated tests of IDM’s infectious diseasemodels. This individual will help support scientific research teams’ adoption of software development practices. This work will ensure that IDM’s scientists can focus on the scientific challenges of disease modeling, with a high level of confidence in the quality of their underlying software. This will require automation ofstatistical tests, collaboration with scientific professionals, and manual exploratory testing. This position reports to the Software Test Manager – IDM.
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The intern for the IDM measles team will collaborate with the researchers on the team to characterize spatial characteristics of measles transmission and disease surveillance networks, aiming to improve IDM's models of disease transmission and produce recommendations relevant to global measles control policies. The intern will work with real-world data, potentially including surveillance of measles cases, serological data on population immunity, and immunization data, to address a number of important questions in measles control. Example questions may include: how spatially sparse is measles disease reporting, and what does this tell us about the value of technological improvements to ease measles case confirmation and reporting? Where do delays arise in existing measles surveillance systems, and how do these delays impact outbreak response activities? What do spatial heterogeneities in measured immunity tell us about how measles travels between communities, and how can models account for these effects to guide local immunization efforts? Outputs will be presented to researchers within IDM, and may also be published in a scientific journal or presented to policymakers at global organizations pursuing measles control efforts (Gates Foundation, CDC, WHO).
The intern will work with IDM's health service delivery researchers, contributing to research into identifying optimal strategies for investing in primary health care and health systems strengthening. The specific project the intern will undertake will be determined based on candidate skill, interest, and institutional need at the time of internship. Examples of potential projects include: analyzing household survey data to quantify patterns of inequality in health intervention coverage and health outcomes; using electronic health records to model continuity of care; analyzing availability using health facility quality data; development of models to represent the health system; identifying and resolving data quality issues in administrative data sources; using linked health facility and population data to diagnose bottlenecks in delivering effective services; estimating health system capacity shortfalls using health worker registry data; incorporating delivery constraints into existing disease transmission models at IDM.
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.
The Computational Sciences group at IDM is focused on the design and implementation of methods and workflows to overcome these challenges. The intern will implement new algorithms and workflows to be used broadly across IDM and by our external network of collaborators.
IDM partners with selected universities, NGOs, government ministries, and other research and public health institutions focused on researching new ways to understand and combat diseases both locally and globally. If you are interested in learning more about collaborating with us, please contact firstname.lastname@example.org.