| The University of Washington (UW) is proud to be one of the nation's premier educational and research institutions. Our people are the most important asset in our pursuit of achieving excellence in education, research and community service. Our staff not only enjoys outstanding benefits and professional growth opportunities, but also an environment noted for diversity, community involvement, intellectual excitement, artistic pursuits, and natural beauty. |
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. IHME aims to provide policymakers, donors, and researchers with the highest-quality quantitative data to make decisions that achieve better health. IHME's research spans multiple disciplines and policy-relevant areas, including resource tracking, cost-effectiveness, forecasting, burden of disease, geospatial analysis, and impact evaluations. It has established international scientific credibility for developing innovative multidisciplinary methods and producing cutting-edge results. IHME aims to be nimble and entrepreneurial in its work, taking on daunting analytic challenges in order to provide critical information that can help answer big-picture questions at the most local levels possible such as:
What is the state of the world's health?
What impact are different programs, initiatives, and policies having on improving health?
What investments and decisions can we make today that will improve health most in the future?
IHME has an outstanding opportunity for a Research Engineer to join the Global Burden of Disease team. The main purpose of this position is to design, implement, and support analytic engines and diagnostics related to the central estimation processes for a myriad of important health indicators. This position will work with researchers in public health, economics, and statistics to create a flexible simulation tool that incorporates a wide variety of data. The position will ensure the routine operation of disease modeling analytic engines and diagnostic tools. He/she will problem-shoot and help modelers find solutions to challenges that arise in undertaking novel analyses. The position will also create new shared functions and tools to meet recurrent challenges and make the overall disease modeling, results review, and finalization process easier and more efficient.
This position requires a strong background in writing scientific software and an ability to translate researchers' needs into a concrete software development plan. The individual will design and implement solutions that improve performance and can easily be utilized by other staff with less coding experience. The position ensures the software developed is appropriately flexible, scalable, and efficient. The position calls for dexterity working with multiple coding languages (e.g., Java, C++, Python, R, SQL).
The individual must learn how multiple components of a complex analytical process relate to one another, learn the nature of the key indicators and variables being analyzed, and identify and implement ways to improve performance while maintaining high-quality and reproducible scientific results. The Global Burden of Disease enterprise has multiple significant components of data intake, analysis, and review. GBD is a systematic, scientific effort to quantify the comparative magnitude of health loss due to diseases, injuries, and risk factors by age, sex, and geography over time. This position lies at the center of critical support for GBD and related activities.
This position may additionally work alongside other teams on complementary projects and will require knowledge and skill sharing and collective problem-solving. Overall, the Research Engineer will be a critical member of an agile, dynamic research team. This position is contingent on project funding availability.
Research learning and methods development
Exhibit command of the dimensions and uses of health data in the Global Burden of Disease (GBD) enterprise.
Become familiar with the various inputs (e.g., disease mortality, incidence, relative risks, covariates, treatment effects, etc.) that the GBD machinery must incorporate.
Gain understanding of the demographic, geographic, and social characteristics in a country that might generate disparities or be useful for population comparisons.
Develop, test, implement, and support analytic methods as appropriate.
Develop a working understanding of epidemiologic methodology and the disease estimation approach of GBD in particular.
Explore new technologies and make recommendations as to their adoption.
Design and articulate ways to improve routine computational processes, including the relevant tradeoffs of different approaches, for decision-making purposes.
Research software development
Translate methods from epidemiologic and statistical researchers into scientific software.
Incorporate statistical optimization/calibration techniques to undertake diagnostics on disease modeling exercises, assess analytic methods for performance, and help troubleshoot modeling exercises with researchers.
Design with flexibility in mind such that more complex models can be built by users over time and so that data intake and the number of outputs can also increase significantly without compromising performance.
Optimize code efficiency and parallelize across our massive (20,000+ CPU cores) computing cluster to enable researchers to quickly produce results.
Create a user-friendly interface for researchers to build, run, and evaluate the results of their own disease models.
Build and implement diagnostics and analytic machinery to undertake other core analytic components of GBD, such as comorbidity adjustments, decomposition of outcomes into multiple causes or risks, and other key central functions.
Follow software development best practices to document, test, and perform source control.
Problem-solve computational and analytic challenges by investigating the data, understanding the root questions, and coming up with alternative measurement strategies.
Maintain, update, and carry out routine but complex computational processes that are central to generating estimates of key health indicators.
Develop and use protocols to identify problems with datasets and routine computational processes, rectify issues, and systematize data for future analyses.
Perform quality checks and audits of code from fellow staff.
Publications, presentations, and data requests
Create tables and figures, and generate text for presentations and publications, drawing upon data and information from a multitude of sources.
Develop novel representations of data and results for senior researchers and other stakeholders.
Communicate clearly and effectively while contributing as a productive member of both the Global Burden of Disease team and the Institute as a whole. Work closely with other team members to help them with relevant tasks, show them how to learn new skills, and help resolve emerging problems on different projects. Attend relevant meetings, adhere to deadlines, and participate as a vital member to collectively advance team-level objectives.
Serve as a resource to others in explaining analytic approaches, describing data, and instructing how to implement code related to demographic estimation.
Participate in overall community of the Institute, carrying out duties as required as team members with other Institute members.
As a UW employee, you will enjoy generous benefits and work/life programs. For detailed information on Benefits for this position, click here.
| Bachelor's degree in Biostatistics, Computer Science, or a related field and two years' related experience in software development, or equivalent combination of education and experience. |
Demonstrated success in implementing code in Python, R, and SQL.
Must have demonstrated facility with analytic tasks and ability to participate productively in interdisciplinary research teams. Strong quantitative aptitude, desire to learn new skills, and ability to interpret complex analytic information.
Strong sense of focus and attention to detail.
Demonstrated familiarity with and ability to agilely assess, transform, and work with quantitative data from a range of sources.
Ability to learn new information quickly and to apply analytic skills to better understand complex information in a systematic way.
Interest in global health research.
Demonstrated organizational skills, self-motivation, flexibility, and the ability to work and thrive in a fast-paced, energetic, highly creative, entrepreneurial environment.
Strong communication skills necessary to discuss complex databases and computation items with lead faculty.
Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.