The Institute for Health Metrics and Evaluation and the Department of Global Health within the School of Medicine and the School of Public Health at the University of Washington are recruiting to fill one full-time year-long postdoctoral fellow appointment.
The Institute for Health Metrics and Evaluation (IHME) is an independent research center at the University of Washington. Its mission is to monitor global health conditions and health systems, as well as to evaluate interventions, initiatives, and reforms. It uses cutting-edge techniques to tackle some of the most difficult and most critical questions in global health and find answers that will become the foundation for better policies and, ultimately, better health.
The successful applicants will have a doctoral research degree (or foreign equivalent) in computer science, statistics, mathematics, or other relevant subject, plus three years related experience or equivalent combination of education and experience.
- Practical experience in one or more of the following: vaccine preventable diseases, statistical inference, stochastic processes, or infectious disease modeling.
- Experience with survey data and administrative data (e.g. HMIS, DHIS2) from health facilities, particularly administrative vaccine coverage data and data from supplemental immunization campaigns.
- Expertise in a second computer programming language or mathematical platform.
Scope of Fellowship
The incumbent(s) will devise and apply innovative methods in geospatial analysis to produce high-quality and policy-relevant estimates of health and health-related indicators at the most granular level possible with a focus on geospatial models of vaccine coverage. Through the development and use of geospatial techniques to synthesize information at the local level, and in partnership with key collaborators around the world, IHME will present results in interactive high-resolution maps to illuminate levels, trends, and disparities in health outcomes.
The incumbent must develop a command of the methods developed and deployed and the rationale for them. In this case, these methods involve the use of model-based geostatistics to model geospatial variation in vaccine coverage and the relationships between vaccine coverage and key health outcomes. These models form a central component of the overall geospatial research program at IHME. The individual is expected to agilely create and deploy code to carry out complex statistical methods. The individual will be a key contributor to discussions about methods development, strategic decision-making about how best to deploy methods using the given computational infrastructure, and most importantly how to improve upon the results given the available data.
Postdoctoral Fellows play a critical role in ongoing research projects that apply analytical approaches and quantitative methods to impact evaluations, health economics, Global Burden of Disease, and other projects within the health metrics field. Duties of each fellow are tailored to create a research experience that builds upon the core proficiencies from their doctoral training.
Fellows work within teams to drive research forward from inception to publication while acquiring analytical skills and exploring new areas of investigation. Along with research opportunities, IHME provides training workshops to broaden fellows’ experience in effective writing for publication, grants, and statistical software programs.
The fellowship program also encourages fellows to engage in meaningful dialogue with the academic and policy communities by presenting research findings at global health conferences and participating in key meetings. This program focuses on defining research and professional development goals for future positons in academia, national health agencies, international organizations, and foundations.
Salary and benefits are commensurate with experience. This is a one-year appointment renewed annually following a performance review.
Applicants should submit a curriculum vitae, a brief statement (500-word limit) outlining research interests and two letters of recommendation.