Wildfire Progression Project
This project is driven by the urgency of addressing the challenges posed by wildfires and harnesses the power of cutting-edge technologies. We are combining the rich information derived from satellite imagery and weather data with an advanced quantum-compatible machine learning technique. Our goal is to enhance the accuracy and timeliness of wildfire predictions, ultimately leading to more effective disaster response and prevention strategies.
- Collect, preprocess, and analyze geospatial data related to wildfire progression.
- Develop and implement machine learning models using PyTorch for wildfire prediction.
- Collaborate with a multidisciplinary team of researchers and scientists.
- Document and present findings to the team and stakeholders.
- Contribute to the development of geospatial analysis tools and pipelines.
- Must be a U.S. citizen.
- Proficiency in geospatial data analysis tools and libraries, including Xarray, GDAL, Rioxarray, and Rasterio.
- Strong programming skills in Python.
- Knowledge of machine learning techniques, with experience in PyTorch preferred.
- Excellent problem-solving and analytical abilities.
- Strong communication and teamwork skills.
- Self-motivated and able to work independently.
Please also apply to the link below