Climate Change AI Innovation Grants 2024
SECTORS :
Climate | AI
GRANTING ENTITIES :
Climate | AI
DEADLINE :
September 15, 2024
TYPE OF SUPPORT :
Research & deployment grant
FUNDING BENEFIT :
150,000 USD
APPLICANTS :
PI must be academia
LOCATIONS :
OECD countries
SYNOPSIS
Artificial intelligence (AI) and machine learning (ML) can help support climate change mitigation and adaptation, as well as climate science, across many different areas, for example energy, agriculture, forestry, climate modeling, and disaster response (for a broader overview of the space, please refer to Climate Change AI’s interactive topic summaries and papers). However, impactful research and deployment have often been held back by a lack of data and other essential infrastructure, as well as insufficient knowledge transfer between relevant fields and sectors.
With the support of Quadrature Climate Foundation, Google DeepMind, and Global Methane Hub, funding is available of up to USD 1.4M for projects at the intersection of AI and climate change - with the support of the Canada Hub of Future Earth.
This program will allocate grants of up to USD 150K for conducting projects of 1 year in duration.
As part of the project, the grantees must publish a documented dataset (or simulator), which was created by collating, labeling, and/or annotating existing data, and/or by collecting, simulating, or otherwise making available new data that can enable further research. We require the dataset to comply with the FAIR Data Principles (Findable, Accessible, Interoperable and Reusable).
Projects are expected to result in a deployed project, scientific publications, or other public dissemination of results, and should include a carefully considered pathway to impactful deployment. All grant IP must be made publicly available under an open license.
This year, there are two special tracks in addition to the main track:
Main Track: Projects in the Main Track should leverage AI or machine learning to address problems in climate change mitigation, adaptation, or climate science, or consider problems related to impact assessment and governance at the intersection of climate change and machine learning.
Special Track on Methane: Submissions to the Special Track on Methane should leverage AI or machine learning to address problems in methane-related climate change mitigation in the short/medium term period (well before 2040).
Special Track on Dataset Gaps: Submissions to the Special Track on Dataset Gaps should have, as their primary focus, the creation of a documented dataset (or simulator) by collating, labeling, and/or annotating existing data, and/or by collecting, simulating, or otherwise making available new data that can enable further research. Topics that may be addressed by the dataset or simulator follow the same scope as submissions to the Main Track, and applicants should highlight the particular gap in dataset availability that this project aims to address, and why this is important for climate change mitigation or adaptation.
For more information & application, click here.