Google.org awards $36m to 17 AI science projects, including Cambridge and MIT

Universities and research organizations will receive funding for projects spanning climate resilience, clean energy, precision medicine and disease research, with access to a six-month Google.org Accelerator

Google.org has selected 17 organizations to receive a combined $36 million for AI-powered scientific research across climate, energy and health

Google.org has selected 17 organizations to receive a combined $36 million through its Impact Challenge: AI for Science, backing projects that use artificial intelligence to advance scientific research. The recipients include the University of Cambridge, Massachusetts Institute of Technology (MIT), University of California, Berkeley and several other universities developing AI applications across climate, energy and healthcare.

The funding follows a global open call launched earlier this year, which attracted applications from across 30 countries. Alongside financial support, the selected organizations can choose to participate in a six-month Google.org Accelerator, providing engineering assistance, technical mentorship and access to Google infrastructure.

The projects range from developing new approaches to battery research and climate modeling to investigating genetic disorders, improving cancer treatment and accelerating drug discovery.

Cambridge, MIT and other universities target climate and energy research

Several of the funded institutions are applying AI to longstanding challenges in energy and environmental science.

The University of Cambridge is developing an approach to predicting degradation in sodium-ion batteries, combining physics foundation models with microscopy to support the development of more durable energy storage technologies.

MIT will focus on automated materials discovery, training AI agents to interpret experimental microscopy images without requiring researchers to carry out every stage of the analysis manually.

Fusion energy is another area receiving support. The Max Planck Institute for Plasma Physics, working with TU Eindhoven, will use physics-informed AI to model the behavior of plasma inside fusion reactors, while the University of Texas at Austin is developing neural network models to accelerate compact fusion reactor design.

Other projects focus on environmental monitoring and climate prediction. UC San Diego is developing an agentic AI pipeline designed to identify interpretable climate physics from Earth observations, build a new climate model and determine where additional ocean observations should be collected.

Inria Chile Research Center is developing a digital twin of Earth's marine ecosystems through a multimodal ocean foundation model. AfriClimate AI Limited is working to identify atmospheric conditions preceding severe storms across Africa, with the aim of extending flash-flood warning times from under three hours to more than six hours.

The University of Washington completes the climate and environmental science group, using natural language to design proteins for sustainability applications, including plastic degradation.

AI research funding targets cancer treatment, genomics and drug discovery

Nine of the selected organizations are working across health and life sciences, with projects examining how AI can support disease research, therapeutic development and more personalized medical treatment.

Australian National University is leading an international collaboration to improve precision oncology and reduce reliance on trial-and-error approaches to chemotherapy.

The University of Cape Town is developing an AI-powered platform to map genetic variation in African drug-metabolizing genes, with the aim of improving treatment selection and safety. Meanwhile, the National University of Singapore will investigate how genetic variants affect RNA splicing across populations to better predict disease impacts.

At the University of California, Berkeley, researchers are developing methods to extract interpretable clinical hypotheses from AI predictions, while New York University Grossman School of Medicine will use AI to identify different forms of DNA damage and investigate previously unknown causes of mutations.

Other recipients include the University of Pittsburgh, which is developing a geometric AI model to compare heart regeneration across species, and the University of Toronto, which is mapping the design space for peptide-based drugs using an AI foundation model.

The AITHYRA Research Institute, working with EPFL, is investigating how viruses manipulate cells and developing an AI-designed protein library to support research into difficult-to-target proteins.

The Allen Institute will focus on designing DNA sequences capable of reaching brain cell types particularly vulnerable to neurodegenerative diseases. It plans to make its models, sequences and research results openly available.

Yossi Matias, Vice President at Google and Head of Google Research, wrote on LinkedIn:

"I am excited to see how these interdisciplinary efforts push the boundaries of scientific discovery for societal impact."

ETIH Innovation Awards 2027 open for entries

The ETIH Innovation Awards 2027 are now open for entries, with 26 categories recognising companies, institutions, projects and individuals making a measurable impact across education technology. The global awards span AI in education, digital learning, higher education, skills and workforce, inclusion, education operations, evidence and impact, with entries managed through ETIH’s new online awards platform.

Entries are open worldwide, with the early-bird deadline on Friday 18 December 2026 and the final entry deadline on Friday 26 February 2027 at 23:59 UK time. 

Explore the 2027 categories and judging criteria, read the How to Enter guide or start an entry through the ETIH Innovation Awards 2027 platform.