This call supports the development of foundation AI models tailored for scientific research in one of four key domains: materials science, climate change, environmental pollution (including PFAS), and agricultural science. The aim is to create open, reusable, and adaptable models that can accelerate scientific discovery, address societal challenges, and promote interdisciplinary collaboration. Projects should demonstrate the model’s utility for specific scientific tasks, ensure open access (including source code and data, where possible), and outline a clear strategy for maintaining and promoting the model to the wider research community.

Expected Outcome:

• Accelerate research and development in science, with focus on the domains of a) materials science, b) climate change science, c) environmental pollution science (including PFAS) and d) agricultural science;
• Advance AI technology (not limited to Generative AI) tailored for scientific needs and potentially adaptable to other tasks in the area of application;
• Contribute to the development of foundation models in the areas of application, and pave the way for future funding of foundation models in a broader range of scientific disciplines;
• Advance solutions to societal or scientific challenges;
• Bridge existing knowledge gaps and induce interdisciplinarity by design across different fields necessary to advance the area of application; and
• Support open-source and open science, especially for research communities with limited access to modern AI tools.