Summary of Duties:
Candidates are sought with expertise in the development and application of numerical air quality models related to air quality, atmospheric chemistry, and climate change at urban, regional or global scales as well as skills in model-data integration. The successful applicant will be expected to help lead the AIRPACT regional air quality forecast modeling system for the Pacific Northwest operated from the Laboratory for Atmospheric Research (LAR) group within the CEE department. This system includes machine-learning models to address regional air quality issues such as wildfire smoke. The selected applicant will be expected to teach and enhance the curriculum in graduate and undergraduate environmental engineering courses, direct graduate student research, and develop a strong extramurally funded research program.
- Technical expertise with one or more of the urban to regional-scale atmospheric chemistry modeling systems applied to air quality, atmospheric chemistry, and climate change.
- Demonstrated interest or expertise in machine-learning approaches to air quality modeling and strong skills in model-data integration.
- Ability to work collegially and collaboratively with diverse range of internal and external constituencies.
- An earned Ph.D. or equivalent degree in a relevant engineering or science field.
- Strong record of scholarship, teaching and professional service.
- An understanding of air pollution permitting and dispersion modeling.
- A demonstrated potential for meeting the expectations of the position through activities such as journal publications, professional conference presentations, teaching experience, outreach, and related activities.