As wildfires increasingly reshape the weather around them, NOAA needs modeling systems that can keep up. As FWI's Satellite Data Assimilation and Fire Weather Modeling Specialist supporting NSSL's Warn-on-Forecast (WoFS) initiative, you will develop and advance convective- and meso-scale atmospheric modeling systems — within the MPAS and/or WRF frameworks — that integrate satellite and in-situ observations through ensemble-based data assimilation to better predict fire behavior, smoke transport, and aerosol impacts. This is high-performance-computing science with real operational stakes: your work will help the National Weather Service better forecast how fire and atmosphere interact.

Work Schedule and Location:

Remote: This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST.

• Develop, modify, and maintain components of advanced atmospheric modeling systems within MPAS and/or WRF frameworks
• Implement and evaluate ensemble-based data assimilation methodologies for integrating satellite and in situ observations into fire, smoke, and aerosol prediction systems
• Conduct research and development activities to improve fire behavior, smoke transport, and aerosol parameterizations in numerical weather prediction models
• Design, execute, and analyze convective- and meso-scale modeling experiments using high-performance computing (HPC) resources
• Develop workflows and software tools using Git, Python, Bash, Fortran, and related technologies to support model development, testing, and evaluation
• Analyze model performance and observational datasets to identify opportunities for improving forecast skill and physical representation of fire-atmosphere processes
• Collaborate with multidisciplinary research teams to support development of next-generation fire and smoke forecasting capabilities
• Prepare technical documentation, code repositories, validation reports, and workflow descriptions to support research and operational activities
• Contribute to project reporting requirements, including quarterly and annual progress reports
• Lead or contribute to peer-reviewed scientific publications and present research findings at national and international conferences, workshops, and stakeholder meetings

Required: 

• MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or a related field
• 8+ years of professional or academic experience

Desired: 

• Experience with convective-scale and/or meso-scale numerical weather prediction modeling
• Demonstrated expertise in ensemble-based data assimilation techniques
• Prior experience in fire, smoke, and/or aerosol modeling and prediction
• Proficiency modifying and developing code within MPAS, WRF, or similar atmospheric modeling frameworks
• Advanced programming experience using Python, Bash, Fortran, Git, and related scientific software tools
• Experience utilizing complex modeling systems in high-performance computing (HPC) environments
• Understanding of aerosol, fire, and smoke parameterization schemes and their application within numerical models
• Demonstrated ability to communicate scientific results through presentations, technical reports, and peer-reviewed publications
• Ability to work effectively as part of an interdisciplinary research and development team

Work Setting and Environment:

• Primary location: Remote
• Normal work hours are Monday through Friday, 8 hours per day / 40 hours per week, excluding federal holidays; field data-collection activities may require irregular hours during active severe weather events
• Local and non-local travel may be required, not anticipated to exceed 5% annually; all unplanned travel must be approved in writing by the COR at least 10 calendar days in advance
• Must complete an online IT security awareness course within one week of starting work
• Foreign national candidates are subject to export control review and require CO/COR approval prior to consideration
• Government-furnished equipment provided, including access to HPC resources, specialized mobile observation platforms, laboratory test equipment, computers, and office workspace, as applicable

$83,000.00 to $87,000.00