We’re standing at a profound inflection point in scientific discovery. AI is ushering in a new era of scientific research, from unraveling the complexities of human disease to forecasting environmental shifts. This work aims to tackle global challenges faster and more effectively than ever before, improving lives everywhere.

Earlier this year, we launched the Google.org Impact Challenge: AI for Science, an open call to organizations harnessing AI for scientific breakthroughs. We received applications across 30 countries, in fields like climate, health, and foundational science.

Today, we’re announcing the 17 selected recipient organizations, which will receive a total of $36 million in funding. Organizations can choose to participate in a six-month Google.org Accelerator, where they will receive engineering support, technical mentorship, and Google infrastructure to transform their ideas into scaled solutions. From advanced energy approaches to decoding the brain, these organizations are pushing the boundaries of scientific discovery for societal impact.

• AfriClimate AI Limited is decoding the atmospheric precursors of deadly storm systems across Africa, aiming to extend flash-flood warning times from under three hours to over six hours.
• Inria Chile Research Center is building a multimodal world foundation model of the ocean by creating a digital twin of Earth's marine ecosystems.
• Massachusetts Institute of Technology is accelerating automated materials discovery by training AI agents to autonomously interpret experimental microscopic imagery.
• Max Planck Institute for Plasma Physics in partnership with TU Eindhoven, is bridging the simulation-to-reality gap for clean fusion energy by using physics-informed AI to model chaotic conditions inside fusion reactors.
• The University of Texas at Austin is developing neural network models to accelerate the design of compact fusion reactors.
• UC San Diego is pioneering an agentic AI pipeline that discovers interpretable climate physics from Earth observations, builds a next-generation climate model, and decides where to collect new ocean observations.
• University of Cambridge is accelerating the development of durable sodium-ion batteries by combining physics foundation models and microscopy to forecast cathode degradation.
• University of Washington is designing proteins with natural language to advance sustainability applications, such as plastic degradation.

• AITHYRA Research Institute, in collaboration with EPFL, is uncovering how viruses manipulate cells and creating an AI-designed protein library to discover therapeutics for undruggable proteins.
• Allen Institute is designing DNA sequences that reach brain cell types more vulnerable to neurodegenerative diseases, openly sharing every model, sequence, and result.
• Australian National University is leading an international collaboration to end trial-and-error chemotherapy and advance equitable precision oncology.
• National University of Singapore is predicting disease impacts by mapping how genetic variants regulate RNA splicing at a population scale.
• New York University Grossman School of Medicine is working to uncover unknown causes of mutations by detecting diverse types of DNA damage using AI.
• University of California, Berkeley is turning black-box predictions into clear clinical biomarkers by extracting interpretable hypotheses from medical AI models.
• The University of Cape Town (UCT) is developing an AI-powered platform to map genetic variation in African drug-metabolizing genes, helping guide clinical drug choices and improve treatment safety.
• University of Pittsburgh is identifying genetic switches to accelerate new cardiac therapies using a novel geometric AI model to compare heart regeneration across species.
• University of Toronto is enabling computer-guided therapeutic drug design by mapping the design space for peptide-based drugs with an AI foundation model.

These organizations represent an exciting range of ideas, disciplines, and approaches to some of the world’s most pressing challenges. We look forward to supporting their work and to seeing what becomes possible when scientific expertise and AI come together to tackle challenges that affect us all.

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