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 a Researcher on the Local Burden of Disease (LBD) project. This project aims to produce estimates of health outcomes and related measures that cover entire continents, but to do so at a very fine, local resolution. Such estimates will allow decision-makers to target resources and health interventions precisely, so that health policy decisions can be tailored for local areas rather than entire countries. A few of the conditions this work will touch on are pneumonia and its etiologies, diarrhea and its pathogens, malaria, child growth failure, HIV/AIDS, tuberculosis, Ebola, and 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.

This position will use model-based geostatistics (MBG) among other innovative analytical methods and devise ways to carry them out more easily and routinely. By enhancing existing computational pipelines and writing novel computational solutions, this position helps resolve challenges to enable the timely and efficient production of high-caliber scientific and policy-relevant results. The solutions developed must allow databases and analytic engines to function seamlessly with one another. This Researcher must develop a command of the methods developed and the rationale for them. They are expected to create and deploy code to carry out complex statistical methods potentially utilized by all team members. This individual will be a key contributor to discussions about 1) statistical and computation methods development, 2) strategic decision-making for implementation of methods into existing computational infrastructure, and 3) ongoing improvements to the architecture of our code base. In addition, this individual will be expected to collaborate with other team members on papers, presentations, and other materials to help disseminate results. This position is contingent on project funding availability.

Responsibilities:

Analyses
• 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 to map health and health-related indicators of substantial global health importance.
• Write, document, test, and run relevant computer code (primarily R with the possibility of Python, C, and C++).
• Maintain, improve, and distribute completed software as part of continuous integration of the LBD software pipeline supporting the geospatial analyses portfolio.
• Coordinate with other teams to integrate methods and results of separate research streams.

General
• Lead discussion in research meetings about results and analyses in order to vet, improve, and finalize results.
• Document code and analytic approaches clearly and systematically for users and other developers.
• 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.
• 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.
• 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.

Minimum Qualifications:
Master’s in statistics, epidemiology, mathematics, engineering, public health, or other related scientific computing field, plus three years’ related experience, or equivalent combination of education and experience.
• Demonstrated success in scientific computing using at least one of the following programming languages: R, Python, C, C++. R strongly preferred.
• Excellent analytical and quantitative skills.
• Ability to independently plan and execute research projects.
• Excellent communication skills, including the ability to present research proposals and results and represent the research group overall.
• Ability to thrive in a fast-paced, team-oriented research environment with a focus on producing innovative, policy-relevant results.
• Demonstrated interest in the research described.

Desired Qualifications:
• PhD in statistics, epidemiology, mathematics, engineering, public health, or other related scientific computing fields.
• Experience with Linux and cluster computing environments.
• Practical experience in one or more of the following: statistical inference, stochastic processes, space-time mathematical models, or infectious disease modeling.
• Experience contributing to a collaborative software project and working with a version control system (git, svn, etc).
• Experience with survey data and administrative data from health facilities.
• Experience in handling spatial data.
• Expertise in additional programming languages or mathematical software packages.

Conditions of employment: Evenings and weekends may be required.