Postdoctoral Scholar in Future Health Scenarios

University of Washington Department of Health Metrics Sciences

United States

Postdoctoral Scholar, Future Health Scenarios - Department of Health Metrics Sciences

Position Overview

Organization: Health Metrics Sciences

Title: Postdoctoral Scholar, Future Health Scenarios - Department of Health Metrics Sciences

Position Details

Position Description

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; Local Burden of Disease; 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 Postdoctoral Scholar to join our Future Health Scenarios team to explore trends in exposure to risk factors. We are looking for someone ready to advance in their career in global health research. The Future Health Scenarios team forecasts GBD inputs and results (burden of more than 350 diseases and injuries and more than 80 risk factors for all GBD geographic locations) to provide policymakers, donors, researchers and the general public with the highest-quality future estimates to make decisions that improve health. As a Postdoctoral Scholar you will be a lead on the Future Health Scenarios team by contributing to research design and training and mentoring junior staff.

IHME researchers analyze and produce key estimates for their assigned research team and 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.

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. This position is contingent on project funding availability. Anticipated start is early Spring 2021.

Postdoctoral Scholar appointments are initially for 12-months with opportunities to renew. Appointment not to exceed 5 years, including postdoctoral experience(s) at other institutions. 

Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria apply. For more information, please visit the University of Washington Labor Relations website.

Responsibilities

  • Be a key member of the Future Health Scenarios team with responsibilities that include: working closely with the faculty team lead on overseeing research and applications, improving and expanding the existing forecasting framework, leading or taking part in writing and statistical analysis of research papers based on the forecasting results, and helping maintain the team’s ability to critically vet the large and detailed interim and final results. 
  • Produce results for the future health scenarios team on non-communicable disease risk factors. Exhibit command of the methodology used in forecasting risk factor exposure, disease burden, and population demographics.
  • Lead and co-author scientific articles in peer-reviewed journals.
  • Develop and implement new computational and statistical methods, with a strong focus on time series analysis of non-communicable disease risk factors (e.g. smoking).
  • 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.
  • Create, test, and use relevant computer code in Python. Maintain, modify, and execute analytic machinery to produce results.
  • Draft presentations, manuscripts, and contribute to funding proposals.
  • Maintain scientific awareness and intellectual agility with data, methods, and analytic techniques.
  • 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.

Condition of employment:.

  • Weekend and evening work sometimes required.

Further information: See IHME’s website: www.healthdata.org

Qualifications

Minimum

  • PhD, MD or foreign equivalent in public health, statistics, biostatistics, math, economics, quantitative social sciences or related discipline plus two years related experience preferred.
  • Growing peer network where sought out as having solid command with engineering/technical areas, a given disease, risk, key indicator, relevant methodological area, and the related data sources and scientific underpinnings.
  • Excellent analytic, critical thinking, and quantitative skills.
  • Experience developing and executing statistical modeling techniques.
  • Demonstrated proficiency in designing, executing, and troubleshooting analytic code in Python and/or R.
  • Results and detail-oriented individual that 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.
  • Demonstrated ability to quickly recognize problems in results and identify root causes in data, methods, and code.
  • 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
  • A long-term interest in a research driven position contributing to the overall mission of our research

Desired

  • Proven interest and some experience in the field of measuring risk factors for non-communicable disease (ie tobacco use), control policies, and methodologies and scientific underpinnings.
  • Experience with machine learning, data mining, and analytic techniques.
  • Experience analyzing data with multi-dimensional array files.
  • Experience writing and executing code in Python.
  • Understanding of and experience modeling with Bayesian methods.
  • Experience mentoring and developing junior employees on soft and technical skills.
  • Experience with project management methods.
  • Peer-reviewed publication record.

Instructions

Applicants should submit a curriculum vitae, a brief statement (500-word limit) outlining research interests and one letter of recommendation via Interfolio :  http://apply.interfolio.com/81828

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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