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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