Start Date: As soon as possible
Radiant Earth Foundation's core mission is to make insights from Earth observations and machine learning an order of magnitude and more accessible for global non-profits, humanitarian organizations, emerging economy governments and others. We are actively working to develop training datasets and models through an open source hub, Radiant MLHub, that supports global missions like agriculture, conservation, and climate change. Radiant Earth also fosters a community of practice to develop standards around machine learning for Earth observation and provide information on the progress and innovation in the Earth observation marketplace.
In addition, we work with organizations on complex use cases with high-impact outcomes. Since our founding in 2016, we've worked with the Bill and Melinda Gates Foundation, Omidyar Network, Schmidt Futures, McGovern Foundation, the World Bank and more.
We are looking for a passionate intern to join our team and work on a novel machine learning application using Generative Adversarial Networks (GAN). The project involves researching latest developments in using GANs on satellite observations as well as designing and implementing different GAN architectures for generating synthetic multi-spectral data.
What we offer:
Due to the restrictions implemented in response to the COVID-19 pandemic, you will be working with the team remotely.
To learn more about Radiant Earth Foundation 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 Foundation is an equal opportunity employer.