Compute for Climate Fellowship 2025 for Tech Startups: (Deadline 6 April 2025)
Details
The Compute for Climate Fellowship is a global R&D funding program that empowers climate tech startups to leverage advanced cloud computing and AI in the fight against climate change.
The Fellowship was founded in 2023 by the International Research Centre on Artificial Intelligence (IRCAI), under the auspices of UNESCO, and Amazon Web Services (AWS). Each Fellow company accepted into the program builds a groundbreaking proof-of-concept (PoC) climate solution that is funded by AWS, with technical and scientific advisors from AWS and IRCAI.
Winners will “think big” and demonstrate innovation, leverage advanced cloud computing, and show potential for significant global impact across at least one of the nine climate solution areas:
- Clean Energy
- Low-Carbon Transportation
- Sustainable Agriculture and Food
- Circular Economy and Industry
- Sustainable Buildings
- Greenhouse Gas Management
- Carbon Removal
- Environment and Climate Risk
- Indigenous Solutions to the Climate Crisis
Benefits of Climate Fellowship
Grants in the form of AWS credits to cover the cloud computing costs of the PoC (up to $200k per startup).
- Three month PoC build period with personalized technical support and mentorship
- Access to advanced computing services, like quantum computing, HPC, and generative AI tools
- Expert guidance in advanced computing, AI, sustainability, and ethics from IRCAI and AWS mentors
- Media and visibility via speaking opportunities and PR (on a case by case basis)
- Showcase of results across United Nations and international bodies
Eligibility
- Your company is privately held and was founded within the last 10 years.
- You have a technical team capable of building with advanced cloud computing.
- Your proposal incorporates innovative use of advanced cloud computing services such as:
- AI/ML and Generative AI
- High-Performance Computing
- Autonomous Computing
- Spatial Computing
- Simulation Technologies
- Quantum Computing
- Time series data analytics
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