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. IHME carries out a range of projects within different research areas including the Global Burden of Diseases, Injuries, and Risk Factors; Forecasting; Costs and Cost Effectiveness; Geospatial Analysis; Resource Tracking; and Impact Evaluations. The aim is to provide policymakers, donors, and researchers with the highest-quality quantitative evidence base to make decisions that achieve better health.
IHME has an outstanding opportunity for a Researcher who will join our Geospatial Analysis team, with a focus on the Pandemics Preparedness Project. This project will identify and define areas at-risk of emerging zoonotic infectious diseases across many of the least prepared countries in the world and present resources so that organizations can begin to quantify and subsequently mitigate this potential. The purpose of this position is to help devise and apply innovative methods in infectious disease modelling to produce high resolution geographic estimates of index case potential and baseline outputs for future pandemic potential estimation for five key pathogen groups: Middle East Respiratory Syndrome Coronavirus (MERS-CoV), the Henipaviruses (specifically Nipah and Hendra virus), Rift Valley Fever, Monkeypox, and Avian Influenza.
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.
The Researcher must develop a command of the methods developed and deployed, and the rationale for them. In this case, the methods include species-distribution and infectious disease modelling, to demonstrate spatial variation in occurrence data; as well as exploring the spatial-temporal relationship between occurrence data and pandemic potential.
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.
- Carry out quantitative analyses and participate in collaborative research projects.
- Undertake innovative applied research and application of models to predict spatial variation in infectious disease prevalence, incidence, and mortality, addressing issues such as sample bias and spatial dependence.
- Develop and implement new computational and statistical methods. Create, test, and use relevant computer code (R, Java, C, C++, or Python). Maintain and distribute completed software.
- Develop new methods for mapping infectious diseases which will include species distribution modelling (SDM).
- 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.
- Support project leaders in the development of new funding proposals 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.
Master’s in epidemiology, public health, computer science, statistics, mathematics, 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, Java, 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.
- Practical experience in one or more of the following: niche models, species distribution models, statistical inference, stochastic processes, or infectious disease modeling.
- PhD in epidemiology, public health, computer science, statistics, mathematics, or related field desired.
- A theoretical and practical understanding of infectious disease epidemiology.
- A theoretical and practical understanding of model-based geostatistics.
- A theoretical and practical understanding of mechanistic modeling.
- Expertise in a second computer programming language or mathematical platform.
Condition of Employment: Evening and weekend work may be required.