Temporary Research ScientistEngineer 3

Job Description

The Civil and Environmental Engineering department has an outstanding opportunity for a temporary Research Scientist/Engineer 3 to join their team.

About this opportunity:

Reporting to Professor Julian Marshall this position will hold the title of Research Scientist and will conduct research on high-resolution air pollution measurement modeling and source characterization.

Key Responsibilities

Quantitative method development and computational modeling (45%)

-Develop implement evaluate and advance computational approaches for estimating spatially and temporally resolved air-pollutant emissions and exposures from observational data.

-Work may include statistical or Bayesian inverse modeling data assimilation optimization uncertainty quantification numerical methods and related approaches.

-Develop methods for integrating observed pollutant concentrations with prior emissions information meteorological information and representations of atmospheric transport.

-Investigate alternative model formulations identify methodological limitations develop solutions to technical problems and improve model accuracy robustness scalability and interpretability.

-Develop and maintain reproducible scientific software and computational workflows.

Analysis and integration of high-resolution air-quality observations (20%)

-Analyze high-resolution environmental datasets including mobile-monitoring and possibly fixed-site air-quality observations.

-Develop and apply methods for combining measurements that differ in spatial and temporal coverage sampling frequency and uncertainty.

-Evaluate spatial and temporal patterns in pollutant concentrations elevated-concentration locations source influences and variability across locations and time.

-Develop approaches for translating heterogeneous monitoring observations into inputs or observational constraints suitable for quantitative modeling and inference.

Mobile-monitoring study design and sampling optimization (15%)

-Contribute to the design of high-resolution mobile-monitoring studies.

-Evaluate tradeoffs among spatial and temporal coverage repeat sampling route length driving time platform availability seasonal and time-of-day coverage and other practical constraints.

-Develop and evaluate quantitative approaches for route design allocation of monitoring effort sampling representativeness and optimization of monitoring resources.

-Assess how alternative sampling designs affect the information that can be obtained about pollution concentrations sources emissions and exposures.

Model evaluation validation and uncertainty analysis (10%)

-Design and conduct numerical experiments sensitivity analyses and validation studies.

-Evaluate model performance robustness identifiability sensitivity to prior assumptions observational requirements and uncertainty.

-Develop cross-validation out-of-sample evaluation or other performance-assessment approaches.

-Assess how monitoring density measurement frequency spatial coverage and combinations of observational datasets affect model performance and inference.

Scientific collaboration and communication (10%)

-Collaborate with faculty investigators research staff students government-agency scientists and external technical partners.

Interpret research findings and communicate methodological choices assumptions limitations and results.

-Contribute to peer-reviewed manuscripts technical reports presentations research proposals project documentation and meetings.

-Participate in research planning and recommend methodological or analytical directions within assigned areas of responsibility.

Required Qualifications

To be considered for thisopportunityyour application mustdemonstrateyou met both the minimum qualifications andadditionalqualifications listed education and/or experience may substitute for minimum qualifications except when there are legal requirements such as license certification and/or registration.

Minimum Qualifications

• Bachelors degree in environmental engineering atmospheric science applied mathematics statistics physics computer science geosciences chemical engineering or another closely related quantitative field
• Four years of experience in at least one area relevant to the research such as data assimilation optimization inverse problems Bayesian methods uncertainty quantification numerical modeling atmospheric transport or dispersion source-receptor modeling spatial statistics or spatiotemporal modeling
• Applicants who do not meet these qualifications WILL NOT be forwarded to the Hiring Manager.

Additional Qualifications

• Demonstrated ability to conduct quantitative computational research.
• Strong scientific programming skills in Python or a comparable scientific-computing environment (e.g. R Julia).
• Strong quantitative reasoning and a foundation in applied mathematics statistics numerical methods or computational modeling.
• Experience in at least one area relevant to the research such as data assimilation optimization inverse problems Bayesian methods uncertainty quantification numerical modeling atmospheric transport or dispersion source-receptor modeling spatial statistics or spatiotemporal modeling.
• Demonstrated ability to formulate technical problems implement computational approaches evaluate results critically and troubleshoot complex scientific or computational problems.
• Ability to learn unfamiliar quantitative methods and scientific concepts and apply them to new research problems.
• Ability to independently move substantial research tasks forward with limited day-to-day supervision while working effectively within a collaborative research team.
• Strong written and oral communication skills.
• Record of peer-reviewed scientific publication appropriate to career stage.

Desired Qualifications

• PhD in environmental engineering atmospheric science applied mathematics statistic physics computer science geosciences chemical engineering or another closely related quantitative field.
• Demonstrated ability to conduct quantitative computational research
• Experience with data assimilation optimization Bayesian inference inverse modeling or related quantitative methods.
• Experience with atmospheric transport dispersion trajectory or source-receptor modeling.
• Experience working with mobile air-pollution monitoring data or other high-frequency geospatial environmental measurements.
• Experience with spatial or spatiotemporal analysis geospatial data integration of observations across spatial or temporal scales or methods for estimating pollutant emissions.
• Experience designing environmental monitoring or sampling studies including questions of representativeness repeated measurements spatial coverage temporal coverage or optimization under resource constraints.
• Familiarity with air-pollution measurement and pollutants such as particulate matter black carbon ultrafine particles nitrogen oxides volatile organic compounds or related pollutants.
• Experience developing reproducible research software working with large scientific datasets or using high-performance computing.
• Experience with air-pollution exposure assessment source attribution or environmental-health applications.

Application Requirement:

Application materials: CV/resume; a brief cover letter (up to two pages) describing relevant quantitative/computational research experience interest in the position and alignment with the job description.

About the Team

The Department of Civil & Environmental Engineering is an academic department within the College of Engineering with over $30M in annual expenditures. The department maintains an internationally recognized research program with six research areas numerous academic programs and multiple research and testing laboratories spread across five different buildings.

The department serves over 800 students annually and grants bachelors masters and PhD degrees. As of January 2026 the department has 35 faculty 11 postdoctoral scholars and 45 staff.

Compensation Benefits and Position Details

Pay Range Minimum:

Pay Range Maximum:

Other Compensation:

Benefits:

Temporary or Regular

FTE (Full-Time Equivalent):

Union/Bargaining Unit:

About the UW

Working at the University of Washington provides a unique opportunity to change lives on our campuses in our state and around the world.

UW employees bring their boundless energy creative problem-solving skills and dedication to building stronger minds and a healthier return they enjoy outstanding benefits opportunities for professional growth and the chance to work in an environment known for its diversity intellectual excitement artistic pursuits and natural beauty.

Our Commitment

The University of Washington is committed to fostering an inclusive respectful and welcoming community for all. As an equal opportunity employer the University considers applicants for employment without regard to race color creed religion national origin citizenship sex pregnancy age marital status sexual orientation gender identity or expression genetic information disability or veteran status consistent with UW Executive Order No. 81.

To request disability accommodation in the application process contact the Disability Services Office at or .

Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law.