Research Scientist (Temporary), Causes of death, Shocks, Intermediate Causes, and Antimicrobial Resistance

As a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem-solving skills, and dedication to build stronger minds and a healthier world.

UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits, and natural beauty.

The Institute for Health Metrics and Evaluation (IHME) is an independent research organization at the University of Washington (UW). 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 (GBD), Injuries, and Risk Factors; Future Health Scenarios; Cost Effectiveness and Efficiency; Resource Tracking; and Impact Evaluations.

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 are 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 Temporary Research Scientist on the Causes of death, Shocks, Intermediate Causes, and Antimicrobial Resistance team. The Causes of Death, Shocks, Intermediate Causes, and Antimicrobial Resistance (AMR) team produces timely, high-impact results that are shared with scientists, collaborators, data providers, global health institutions, and government officials to inform policy, publications, and funding decisions. The cause of death sub-team collects all medically verifiable cause of death data, corrects for known biases and compiles it into a comprehensive, comparable, and detailed database used in the Global Burden of Disease study. The AMR sub-team estimates the global burden of drug-resistant and susceptible infections, including their geographic distribution and clinical impact. Both sub-teams rely on diverse data sources, such as records of multiple or intermediate causes of death and linked patient or diagnosis data, to study patterns in cause co-occurrence across death and disease. These shared data sources connect the team’s work across its different content areas.

We are seeking a candidate with strong quantitative and statistical modeling skills, particularly in Bayesian methods, who is ready to advance their career in global health research. The Research Scientist (IHME Research Scientist 2) is critical to supporting the development and integration of key components of AMR estimates, including modeling the prevalence of resistance and antibiotic consumption in data-sparse environments. In this role, you will contribute to research design, lead and mentor junior staff, and oversee the development and implementation of complex modeling methods and pipelines. You will work with a wide range of data sources—such as laboratory and microbiology data, healthcare claims, surveys, vital registration, literature, and administrative records—to produce, critique, and improve estimates that inform global health policy. You are someone who thrives in a collaborative, fast-paced environment, can manage multiple projects simultaneously, and is committed to scientific rigor and innovation. With a strong publication record, you will continue to expand your portfolio through peer-reviewed research and contribute to IHME’s mission of delivering timely, relevant, and scientifically valid evidence to improve health outcomes worldwide.

We are looking for someone ready to advance in their career in global health research. As a Research Scientist, you will be contributing to research design and training, leading, and/or mentoring junior staff. IHME researchers 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.

You will be integrally involved in producing, critiquing, improving, and disseminating results. You are someone who is capable of keeping your team on track to meet deadlines and research objectives. You already have a publication record, 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.

Responsibilities:

• Exhibit command of the team’s research areas, including the methodology and its components.

• 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 datasets to be used in epidemiological and statistical analyses.

• Develop and implement new computational and statistical methods. Write, test, and maintain code primarily in Python (preferred) and/or R, with a willingness to learn and adapt to additional programming languages as needed. Maintain, modify, and execute analytic machinery that generates results.

• Assist in drafting presentations and manuscripts, and contribute to the preparation of funding proposals.

• Lead and co-author scientific publications in peer-reviewed journals.

• Maintain scientific awareness and intellectual agility with data, methods, and analytic techniques.

• May lead and/or mentor junior staff.

• Contribute ideas and content for internal and external training materials to enhance understanding and effective use of IHME tools and data. May participate in teaching established trainings.

• Contribute to research design.

• Other duties as assigned that fall within reasonable scope of research team.

Minimum Qualifications:

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

Additional Qualifications:

• Extensive experience in statistical modeling, particularly in Bayesian methods, with demonstrated ability to apply modeling techniques to data-sparse environments.

• Demonstrated ability to quickly and independently recognize and troubleshoot problems in results and identify root causes in data, methods, and code.

• Experience and demonstrated ability developing and maintaining complex computational workflows, including data processing, model development and vetting.

• Experience working with large, multidimensional datasets, including strategies for data cleaning, transformation, and file management.

• Advanced proficiency in coding with R and/or Python is required. Python is preferred, but candidates with strong R skills and a willingness to learn Python on the job will be considered.

• Ease and experience pushing code in a team environment, with experience using GIT in a team environment.

• Extensive experience and ability to create and interpret data visualizations to identify errors, patterns, diagnose anomalies, and assess the reliability of novel analytical results.

• Growing peer network where sought out as having solid command of 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.

• 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.

• Excellent written and oral communication skills required, including track record of success in co-auhorship on multiple scientific papers, presenting results, and representing research at meetings.

• Demonstrated ability to contribute to and sustain collaborations with external research teams.

• 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 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: https://www.healthdata.org/about/dei.

Desirable Qualifications:

• MD or PhD in public health, epidemiology, statistics, biostatistics, math, economics, or quantitative social sciences plus two years’ experience preferred.

• Experience with machine learning, data mining, and analytic techniques.

• Experience researching antimicrobial resistance, infectious diseases or infection control or other interventions such as WASH or vaccinations.

• Experience mentoring and developing junior employees on soft and technical skills.

• Peer-reviewed publication record.

Conditions of Employment:

• Weekend and evening work sometimes required.

• This position is open to anyone authorized to work in the US.

• Working internationally is only allowed for IHME sponsored work that requires in -country participation.

• Office is located in Seattle, Washington. This position is eligible to work fully remote in the US; work schedule required to overlap 50% of IHME office hours, between 8 a.m. and 6 p.m. Pacific Time as agreed upon between employee and supervisor.

• This position currently has 12 months of funding with a possibility of being extended.