The Institute for Health Metrics and Evaluation (IHME) is an independent research center at the University of Washington. Its mission is to deliver to the world timely, relevant, and scientifically valid evidence to improve health policy and practice. IHME carries out its mission through a range of projects within different research areas including the Global Burden of Diseases, Injuries, and Risk Factors; Future Health Scenarios; Costs and Cost Effectiveness; Resource Tracking; and Impact Evaluations. Our vision is to provide policymakers, donors, and researchers with the highest-quality quantitative evidence base so all people live long lives in full health.

IHME is committed to providing the evidence base necessary to help solve the world’s most important health problems. This requires creativity and innovation, which is cultivated by an inclusive, diverse, and equitable environment that respects and appreciates differences, embraces collaboration, and invites the voices of all IHME team members.

IHME has an excellent opportunity for a Researcher to join our team working on the intersection of human and animal health. IHME researchers analyze and produce key estimates for their assigned research team and will assess all available quantitative data – including those on causes of death, epidemiology, and a range of determinants such as education and income – from surveys, vital registration, censuses, literature, registries, and administrative records. Using established modeling tools and through creation of novel code, researchers incorporate all relevant data to produce the most up-to-date and scientifically credible results. As part of the Global Burden of Animal Diseases (GBADs) project https://animalhealthmetrics.org/ we are working to examine the existing evidence base for determining the global burden of zoonotic pathogens, collating and analyzing available data to inform future burden estimation efforts, and promote further data collection for locations or specific metrics currently underrepresented in current health estimation datasets.

Within the GBADs human health theme, IHME, along with collaborators at Sciensano https://www.sciensano.be/en, will be using a variety of methods, including systematic literature reviews, meta-analytic tools, and statistical modeling to examine the current state-of-the-art for zoonotic disease burden estimation, focusing on pathogens with livestock reservoirs and with implications for food safety. The aim is to determine the extent to which existing pathogen-specific estimates can be enhanced by supplementing existing databases with new data, or novel collection of additional data related to, but not limited to, disease duration and severity. For pathogens where there are limited global estimation efforts, the work will focus on determining the feasibility of future estimation efforts by surveying the current data landscape for key burden measures such as mortality, prevalence, and incidence, as well as ancillary metrics. Finally, the project will work to develop methods by which food safety metrics could be integrated within existing burden of disease estimation efforts. Extraction of new data will be in tandem with methodological innovation and analysis so that further data extraction can be refined and focused on current data gaps and missingness.

You will be integrally involved in producing, critiquing, improving, and disseminating results. You already have a command of epidemiology, statistics, disease modeling, or related interests, and we will help you develop an understanding of our core research and methodology. Our researchers work with senior research leads and external collaborators and take part in the intellectual exchange about how to improve upon and disseminate the results.

You are expected to interact successfully with a wide range of partners and to describe complex concepts and materials concisely. Overall, Researchers are critical members of agile, dynamic research teams. This position is contingent on project funding availability.

Responsibilities

• Develop a core understanding of zoonotic disease burden data collection and estimation methodology and its components.
• Conduct literature reviews to supplement current geographic and metric-specific data gaps.
• Under the guidance of experienced scientist and/or faculty, carry out quantitative analyses and statistical modeling to produce results designated on a given timeline as part of collaborative research projects.
• Extract data from various sources and databases. Format, transform, review, and assess data sources to determine their relevance and utility for ongoing analysis. Understand key data sources and variations in these across and within countries.
• Review, assess, and improve results and methods.
• Apply computational and statistical tools and algorithms for the preprocessing, analysis, and visualization of source data.
• Document code and analytic approaches systematically so that analyses can be replicated by other team members.
• Lead discussion in research meetings about results and analyses to vet, improve, and finalize results.
• Contribute to creation of presentations, manuscripts, and funding proposals. Co-author paper(s).
• Maintain scientific awareness and intellectual agility with data, methods, and analytic techniques.
• Other duties as assigned that fall within reasonable scope of research team.

REQUIREMENTS

• Master’s degree in public health, epidemiology, veterinary medicine, statistics, biostatistics, math, economics, quantitative social sciences, or related discipline plus 1 year related experience, or equivalent combination of education and experience.

Additional Requirements:

• Proven interest and some experience in zoonotic diseases, burden estimation, or statistical analyses of disease data, and the related data sources and scientific underpinnings.
• Strong analytic, critical thinking, and quantitative skills.
• Ability to professionally and effectively communicate and work with other staff at all levels in order to achieve team goals for the analyses and related outputs.
• Results- and detail-oriented individual who can initiate and complete tasks under tight deadlines and changing priorities both independently and in a team environment. Flexibility with hours and workload is key.
• Working ability with at least one statistical programming language (preferably R; Python acceptable).
• Excellent communication skills, both oral and written.
• Ability to work both independently and in collaboration with a team.
• A long-term interest in a research scientist position contributing to the overall mission of our research.

A commitment to working to alongside others at IHME to illuminate the health impacts of systemic racism and to work within IHME to make our organization more diverse and inclusive. See IHME’s DEI statement here: http://www.healthdata.org/get-involved/careers/dei.

Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.

DESIRED

• Proven track record in undertaking literature reviews and their analysis, including meta-analysis methods.
• Prior work on collaborative open data projects and methodologies, such as work with Github repositories, or Living Systematic Reviews.
• Track record of success in co-authorship on scientific papers, presenting results, and representing research at meetings.
• Knowledge of machine learning, data mining, and analytic techniques.

CONDITIONS OF EMPLOYMENT

• Weekend and evening work sometimes required.
• This position is open to anyone authorized to work in the U.S. The UW is not able to sponsor visas for staff positions.
• Office is located in Seattle, Washington. This position is eligible to work fully remote in the U.S.; work schedule required to overlap 50% of IHME office hours, between 8 a.m. and 6 p.m. Pacific Time.
• This position currently has funding till December 2023, with a possibility of being extended.
• Committed to attracting and retaining a diverse staff, the University of Washington will honor your experiences, perspectives and unique identity. Together, our community strives to create and maintain working and learning environments that are inclusive, equitable and welcoming.

Application Process:
The application process for UW positions may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Workforce Authorization, Cover Letter and/or others. Any assessments that you need to complete will appear on your screen as soon as you select “Apply to this position”. Once you begin an assessment, it must be completed at that time; if you do not complete the assessment you will be prompted to do so the next time you access your “My Jobs” page. If you select to take it later, it will appear on your "My Jobs" page to take when you are ready. Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.