Next-generation wildfire risk assessment using deep learning based high resolution fuel maps and stochastic fire spread modeling

About the role

This project aims to develop a next-generation wildfire risk assessment platform that tightly integrates Earth Observation (EO) data, deep learning, and dynamic fire behavior modeling.

Responsibilities

• Design and train advanced deep learning models (e.g., U-Net, Vision Transformers) using multi-modal EO datasets (optical, radar, thermal, LiDAR) to generate high-resolution fuel maps.
• Apply explainable AI techniques to interpret model behavior.
• Couple fuel products with stochastic fire spread simulators to quantify wildfire behavior (e.g., burn probability, fire intensity) under varying weather scenarios.
• Explore how simulation-derived metrics can enhance EO-based foundation models for wildfire risk assessment.
• Deliver a probabilistic, integrated wildfire risk metric through an interactive, stakeholder-focused visualization platform.

Requirements

• Strong background in data science, machine learning, remote sensing, wildfire science, or a related field.
• Experience with deep learning frameworks, satellite observations (e.g., Sentinel, Landsat, NASA products), and/or geospatial analysis is highly desirable.
• Familiarity with fire behavior modeling, uncertainty quantification, or explainable AI methods is a plus.
• Strong programming skills, quantitative reasoning, and ability to work independently in a collaborative, interdisciplinary research environment.

Qualifications

• Doctoral Degree.

Skills

• Data Science
• Machine Learning
• Remote Sensing
• Wildfire Science
• Deep Learning Frameworks
• Satellite Observations
• Geospatial Analysis
• Fire Behavior Modeling
• Uncertainty Quantification
• Explainable AI Methods
• Programming Skills
• Quantitative Reasoning

Benefits

• Unique research opportunities at NASA Centers, Headquarters, or affiliated research institutes.
• One to three-year fellowships designed to advance NASA’s missions in various scientific fields.

Pay

• Competitive salary commensurate with experience.

Schedule

• Full-time position.

Contact Information

For questions about this opportunity, please email npp@orau.org.

To apply, visit the NASA Postdoctoral Program website for application instructions and requirements.