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. IHME carries out 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; Local Burden of Disease (LBD); 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.
Scope of Fellowship
IHME has an excellent opportunity for a Postdoctoral Fellow to join the Local Burden of Disease team.The LBD 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. Through the development and use of geospatial techniques to synthesize information at the local level, and in partnership with key collaborators around the world, the LBD will produce and present results in interactive, high-resolution maps to illuminate levels, trends, and disparities in health outcomes.
The Postdoctoral Fellow 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 individual will also be responsible for contributing to papers, presentations, and other materials to help disseminate results.
Postdoctoral Fellows analyze and produce key estimates for their assigned research team and will assess all available relevant 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. Candidates possessing specific interests in pneumonia and its etiologies, diarrhea and its pathogens, malaria, child growth failure, HIV/AIDS, tuberculosis, Ebola, as well as neglected tropical diseases, and expertise in developing models in any of these, are strongly encouraged to apply.
You will be integrally involved in producing, critiquing, improving, and disseminating results. You are someone that is capable of keeping your team on track to meet deadlines and research objectives. You have experience with the publication process, and at IHME you will build out your portfolio with several peer-reviewed papers. You thrive in a collaborative work environment and are capable of working on multiple projects concurrently while meeting deadlines. You keep current of recent scientific, engineering and technical advances and are able to translate these into your research. Along with research opportunities, IHME provides training workshops to broaden fellows' experience in effective writing for publication, grants, and statistical software programs. This position is contingent on project funding availability.
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 positions in academia, national health agencies, international organizations, and foundations.
Salary and benefits are commensurate with experience. This is a one-year appointment; possible extension dependent upon funding.
The University of Washington and the International Union, Automobile, Aerospace and Agricultural Implement Workers of America, Local 4121 (UAW 4121) currently are negotiating their first collective bargaining agreement for Postdoctoral Scholars. Employees in this title are represented by UAW 4121 and will be subject to the applicable collective bargaining agreement, unless agreed exclusion criteria apply. For more information and updates on the bargaining process, please visit https://hr.uw.edu/labor/unions/uaw/postdoc-negotiation-updates.
Exhibit command of correlated data modeling (e.g. spatial, temporal, or random effects models), including the methodology and its components. If lacking direct experience with model based geostatsitics, rapidly acquire methodological and applied spatial modeling knowledge.
Independently carry out quantitative analyses and participate in reciprocal research projects. Interpret and vet results from junior staff, formulate conclusions and inform team leaders.
Develop, quality check, and distribute complex data sets to be used in epidemiological and statistical analyses.
Develop and implement new computational and statistical methods. Create, test, and use relevant computer code (mainly R, with the possibility of Python, C++, SQL or equivalent). Maintain, modify, and execute analytic machinery.
Draft presentations, manuscripts, and contribute to funding proposals. Lead and co-author scientific articles in peer-reviewed journals.
Maintain scientific awareness and intellectual agility with data, methods, and analytic techniques.
Oversee staff to include: hiring and training; leading workflow; priority setting; critiquing work and establishing quality standards; conducting regular performance assessments, providing mentorship and professional development for employees.
Provide ideas and content for the development of internal trainings. Teach established trainings.
Contribute to research design.
Other duties as assigned that fall within reasonable scope of research team.
The successful applicants will have a doctoral research degree (or foreign equivalent) in computer science, statistics, mathematics, epidemiology, evolutionary biology, or other relevant subject, plus three years' related experience or equivalent combination of education and experience.
Excellent analytic, critical thinking, and quantitative skills.
Results and detail-oriented individual that can initiate and complete tasks under tight deadlines and changing priorities both independently and in a team environment.
Experience devising and executing statistical modeling techniques.
Demonstrated ability to quickly recognize problems in results and identify root causes in data, methods, and code.
Ease in designing, executing, and troubleshooting code in one or more languages (e.g. R, Python, C++).
Excellent written and oral communication skills required, including track record of success in co-authorship on multiple scientific papers, presenting results, and representing research at meetings.
Ability to work both independently and in collaboration with a team.
Experience with machine learning, data mining, and analytic techniques.
Experience mentoring and developing junior employees on soft and technical skills.
Practical experience in one or more of the following: statistical inference, stochastic processes, space-time mathematical models, or infectious disease modeling.
Experience with survey data and administrative data (e.g., HMIS, DHIS2) from health facilities.
Experience with spatial data objects (e.g. shapefiles, rasters)
Experience with project management methods.
Peer-reviewed publication record.
Applicants should submit a curriculum vitae, a brief statement (500-word limit) outlining research interests and two letters of recommendation.
Equal Employment Opportunity Statement
University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, marital status, pregnancy, genetic information, gender identity or expression, age, disability, or protected veteran status.
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