The Institute for Health Metrics and Evaluation (IHME) is an independent research center at the University of Washington focused on expanding the quantitative evidence base for health. 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. IHME is seeking to revolutionize the way we track diseases around the world by developing innovative geospatial analytic methods to produce increasingly granular estimates of diseases and determinants.
IHME has an outstanding opportunity for multiple Researchers whose work will focus on model based geostatistics (MBG) on our Local Burden of Disease team. The purpose of these positions is to help 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.
The Researcher will be a critical member of an agile and dynamic research team developing new approaches and producing detailed estimates that will empower policymakers and donors to make optimal decisions about allocating funds and prioritizing interventions. The individual will be expected to interact successfully and describe complex concepts and materials concisely to a wide range of stakeholders, including high-level individuals in government or other organizations.
Just a few of the conditions this work will touch on include pneumonia and its etiologies, diarrhea and its pathogens, malaria, child growth failure, HIV/AIDS, tuberculosis, Ebola, as well as neglected tropical diseases. 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 Researcher must develop a command of the methods developed and deployed and the rationale for them. 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.
The individual will also be responsible for contributing to papers, presentations, and other materials to help disseminate results. This position is contingent on project funding availability.
- Carry out quantitative analyses and participate in collaborative research projects.
- Undertake innovative applied research and application of model based geostatistics, addressing issues such as sample bias and spatial dependence with an emphasis on improving predictive performance.
- Develop and implement new computational and statistical methods. Create, test, and use relevant computer code (primarily R with the possibility of Python, C, and C++). Maintain, improve, and distribute completed software.
- Develop new methods to map health and health-related indicators of substantial global health importance.
- Review and assess data sources in order to determine their relevance and utility for ongoing analyses. Become expert in understanding key data sources and, in particular, variations in these across and within countries.
- Communicate with external collaborators in order to best understand the nature, key characteristics, and context of the data, engage in critiques of the analytic results, and disseminate findings.
- Develop and maintain relationships with designated collaborators. Respond to and, as appropriate, integrate feedback from collaborators into the analyses. Work directly with collaborators to understand data to which they have access, and to in turn help them understand the methods being applied. Help to manage and orchestrate joint strategies for analysis.
- Assess and coordinate with others on the integration of analytic methods into computational machinery and with evolving databases so that the results can be produced as part of an overall system supporting the geospatial analyses portfolio and be used in conjunction with results from other research streams at IHME.
- Be an effective communicator with other staff on the project of varying levels, disciplines, and authority to achieve team goals for the analyses and related outputs.
- Contribute and develop ideas for new research projects.
Publication and dissemination
- Write and lead publication of research findings in national and international peer-reviewed journals and other publications.
- Present papers at national and international conferences to disseminate research findings.
- Represent the research group and the Institute at external meetings, seminars, and conferences.
- Lead discussion in research meetings about results and analyses in order to vet, improve and finalize results.
- Document code and analytic approaches systematically so that analyses can be replicated by other team members.
- Become a fully contributing member to the IHME team overall, lending help and support where needed, participating in mutual intellectual critique and development with colleagues, leading trainings where relevant, and acting as a mentor to more junior staff contributing to the research process.
Masters in computer science, statistics, mathematics, epidemiology, ecology, evolutionary biology or other relevant subject, plus three years related experience or equivalent combination of education and experience.
- Demonstrated interest in the research described.
- Experience in and demonstrated success in scientific computing using at least one of the following programming languages: R, Python, C, C++.
- Experience in handling point, polygon and raster spatial data.
- Excellent analytical and quantitative skills.
- Good publication record.
- Ability to independently plan and execute research projects.
- Excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings.
- Ability to thrive in a fast-paced, team-oriented research environment with a focus on producing innovative, policy-relevant results.
- PhD in computer science, statistics, epidemiology, mathematics or related field
- Practical experience in one or more of the following: statistical inference, stochastic processes, space-time mathematical models, or infectious disease modeling
- Experience with survey data and administrative data (e.g. HMIS, DHIS2) from health facilities
- Expertise in R
- Expertise in a second computer programming language or mathematical platform
Condition of Employment: Evening and weekend work may be required.