Radiant.Earth launched operations in August 2016 to answer the call for open access to geospatial data, with analytical tools for global development practitioners designed to improve decision-making, and to foster entrepreneurship worldwide. Radiant. Earth’s geospatial technology platform will permit users to illuminate earth, literally, to allow everywhere to be seen to turn the telescopes back on human activity as we enter the Anthropocene period; and to give decision-makers a scientific window into understanding global activity better. Providing the global community with these tools and data can create powerful insights and accelerate greater catalytic, evidence-based support for change.
What You Will Do:
• Become familiar with different remote sensing imagery on Radiant.Earth Platform
• Construct deep learning classification models and apply them to large-scale satellite imagery at global scale
• Construct predictive models using satellite imagery for agricultural and drought prediction applications
• Report on weekly work progress and prepare final presentation
• Candidates must be currently enrolled in an accredited academic program (preferably pursuing a Master’s or Doctoral degree) in Computer Science, Remote sensing, Geography, Environmental Science, Atmospheric Science or a related discipline
• Basic knowledge of machine learning and deep learning techniques
• Experienced in Python programming
• Experienced working with one or more of the following libraries: TensorFlow, Caffe, OpenCV, and scikit-learn
• Experience in mass processing and analysis of remote sensing data on AWS
• Experience working with geospatial libraries in Python including GDAL and Rasterio
To learn more about Radiant.Earth’s platform visit www.radiant.earth.
While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted. All applications are considered confidential. Radiant.Earth is an equal opportunity employer.