The Institute for Health Metrics and Evaluation and the Department of Health Metrics Sciences within the School of Medicine 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.
IHME has an exciting opportunity for a Postdoctoral with a focus on cardiovascular diseases as part of the GBD enterprise. The individual will work with data from multiple sources including vital registration, scientific literature, disease registries, and hospital records. The individual will focus on improving the machinery and analytic framework used in estimation of the local and global burden of cardiovascular risk factors and diseases. The Fellow will work primarily on the cardiovascular team, but will also interface with other teams and internal and external partners. He/she will need to be adept at translating complex analytic aims into functional and efficient code that can be operated routinely as part of the overall GBD machinery.
The individual will need to become familiar with the epidemiology of multiple cardiovascular risks and diseases and how these relate to the overall GBD principles and methods. An ability to efficiently review and interpret epidemiologic scientific literature will be particularly valuable; however, no prior experience with cardiovascular disease is required. The Researcher will need to understand how best to integrate very large databases, complex computer-based statistical disease models, model diagnostics, and the best principles of reproducible data science. He/she will be expected to help interpret and improve upon the results of the methods.
The overall GBD enterprise produces estimates for more than 300 diseases and injuries and more than 70 risk factors for greater than 500 geographic locations. The Fellow will be integrally involved in producing, critiquing, improving, and disseminating results. The individual must develop an understanding of the GBD methodology and must already have a strong command of either epidemiology, statistics, disease modeling, or related fields. The individual will work with senior research leads and take part in the intellectual exchange about how to improve upon the results and in creating papers and presentations that help share the results with broader audiences. Strong written and verbal communication skills are expected.
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.
Overall, the individual will be a critical member of an agile, dynamic research team. This position is contingent on project funding availability.
Research command and analyses
Develop a core understanding of the Global Burden of Disease methodology and its components, especially those related to causes of death estimation.
Formulate analytic strategies and carry out quantitative analyses. Test different analytic approaches. Interpret and improve the results.
Translate complex analytic aims into efficient and effective code.
Identify, review, and assess data sources in order to determine their relevance and utility for ongoing analyses. Develop maps for use in translating data from different formats and classification systems. Review, extract and standardize data.
Manage and complete large-scale prospective reviews of the scientific literature.
Analyze data to inform various disease estimation efforts, examples including estimation of intermediate causes of death (heart failure, etc.), estimation of the contribution of atrial fibrillation to stroke, or estimation of heart failure due to reduced or preserved ejection fraction. This will include developing and interpreting mixed effects regression-based models.
Develop and implement new computational and statistical methods. Create, test, and use relevant computer code (R, Python, SQL or equivalent). Maintain, modify, and execute analytic machinery that results.
Develop and implement diagnostics by which to assess both data and results.
Communicate with external collaborators in order to best understand the nature, key characteristics, and context of the data and engage in critiques of the analytic results.
Collaborate with and gather feedback from multiple senior faculty
Effectively communicate and work with other staff at all levels in order to achieve team goals for the analyses and related outputs.
Explore varied analytic approaches and coding techniques to improve upon results (e.g. machine learning, using linkage data for analysis, etc).
Contribute to papers and presentations of the research findings.
Lead research meeting discussions about results and analyses.
Document code and analytic approaches systematically so that analyses can be replicated by other team members.
Train other team members in techniques and tools.
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, and acting as a mentor to more junior staff contributing to the research process.
As a UW employee, you will enjoy generous benefits and work/life programs. For detailed information on Benefits for this position, click here.
PhD in public health, epidemiology, statistics, biostatistics, or related field
Disease and/or risk-specific expertise, including familiarity with data sources and epidemiology. Prior experience with cardiovascular disease is helpful but not required.
Demonstrated interest in the research described.
Experience of and demonstrated success in using at least one of the following programming languages: Python, R, SQL or equivalent.
Excellent analytical and quantitative skills.
Ability to undertake research projects with limited guidance.
Excellent communication skills, including track record of success in writing for publication, presenting research proposals and results, and representing research groups at meetings.
Ability to thrive in a fast-paced, team-oriented research environment with a focus on producing innovative, policy-relevant results.
Applicants should submit a curriculum vitae, a brief statement (500-word limit) outlining research interests and one letter of recommendation.
University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.
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