The School of Environmental and Forest Sciences is seeking a remote sensing Research Associate to lead the improvement of smoke forecasting tools that support wildfire incidents throughout the United States. The Research Associate will lead an effort to mine, analyze, synthesize, and deliver remotely sensed earth observations in various formats to personnel deployed to wildland fire incidents, health and air quality agencies, and the public.
This project is conducted jointly by the US Forest Service AirFire Research Team and the University of Washington, School of Environmental and Forest Sciences. The project leads are Susan O'Neill (USFS), Sim Larkin (USFS / UW), and Ernesto Alvarado (UW).
Identifying gaps in the current use of satellite data for wildland fire incidents.
Formulating strategies for additional use of satellite data for these incidents.
Integrating satellite data into the BlueSky smoke modeling framework, particularly to improve emissions, plume rise, and model output evaluation.
Identifying future opportunities as new satellite systems launch and data come online.
The work will be conducted as part of the multidisciplinary team, integrating data from many sources and disciplines such as fire ecology, atmospheric chemistry, fire weather, fire behavior and combustion, and field campaigns of land and airborne measurements. The basic existing modeling system is the BlueSky smoke modeling framework, which links together fire activity, mapped fuel loadings, fuel consumption and emission models, and algorithms for fire spread and vertical allocation emissions into dispersion and atmospheric chemistry models to produce smoke forecasts. The successful candidate will serve as the resident satellite data expert for the Team regarding how remotely sensed data can be used in our existing systems, help develop new innovative uses/applications, and facilitate delivery of remotely sensed data to our users and customers.
The position will provide an outstanding opportunity to apply a variety of field and analytical skills to perform original and applied research, present the results at scientific meetings and trainings, and publish first-author papers in peer-reviewed journals. The appointment is for one-year renewable up to three years. The salary is negotiable depending upon experience and includes benefits and a travel budget. The initial appointment will be for 1yr, with the 2nd year conditional on performance. The position is located at the Pacific Wildland Fire Sciences Laboratory in Seattle, Washington, USA and is funded by the U.S. Forest Service and through a NASA grant.
Ph.D. (or foreign equivalent), using remote sensing in atmospheric science, engineering, or related field
Knowledge of available remotely sensed products, experience manipulating the data, and benefits/drawbacks of different approaches and algorithms.
Strong quantitative skills and familiarity with statistical techniques used in remote sensing and atmospheric sciences.
Experience with manipulating and analyzing large spatial datasets
High-level R and/or Python programming skills
Comfort in working in UNIX/LINUX environment
Data and workflow management skills
Strong writing and presentation skills, including a track record of peer-reviewed publications and scientific conference presentations
Ability to work in a collaborative environment across many disciplines
The UW and School of Environmental and Forest Sciences promote diversity and inclusivity among our students, faculty, staff, and public. Thus, we are strongly seeking candidates whose experiences have prepared them to fulfill our commitment to inclusion and have given them the confidence to fully engage audiences from a wide spectrum of backgrounds.
University of Washington faculty engage in teaching, research, and service.
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University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.
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