AI Scientist: Funded projects
Backed by £6 million over 9 months, these projects will test whether AI systems can plan and run scientific experiments in the real world.
Explore the research
These projects reflect a striking diversity of technical approaches, from neurosymbolic models to vision-language systems for robotics. Projects span the UK, the US, and Europe, bringing together major platforms, leading universities, and emerging startups.
Together, these teams are tackling a wide range of physical scientific challenges, including:
- Life sciences: autonomously discovering Alzheimer’s therapeutics, improving cancer vaccines, and inventing new genetic regulatory systems.
- Materials science: optimising quantum dot compositions for next-generation displays.
- Energy: uncovering the mechanisms that govern battery longevity.
As AI systems make hypothesis generation increasingly abundant, the bottleneck in science is shifting toward validation: the physical capacity to test ideas in the real world.
These projects are structured as nine-month sprints designed to probe the limits of AI-driven discovery. Can AI Scientists recover when experiments fail? Can they identify interdisciplinary opportunities that human researchers might overlook? To answer these questions, each project will pursue two challenges: one the system is expected to solve, and one where it is likely to struggle.
Amina: Autonomous AI Scientist for Rapid Pathogen Diagnostic Design
Abhi Rajendran, AminoAnalytica
Wet-Lab-First AI Scientist
Katya Putintseva, Briefly Bio
Silico Habilis
Garik Petrosyan, Deep Origin
Automated Elucidation of Mechanisms Driving Age-Related Lysosome Failure
Michaela Hinks, Edison Scientific + Mathieu Bourdenx, University College London
AI-Driven Cell-Free Energy Development and Optimisation
Scott Riggs, Find What Matters + Anton Jackson-Smith, b.next
ThetaWorld
Otter Quarks
Towards a Self-Reflective AI Scientist for Autonomous Sustainable Microbial Protein Biomanufacturing
Miao Guo, King’s College London
Putting a (Better) Brain in the Mobile Robotic Scientist
Andrew I. Cooper + Gabriella Pizzuto, University of Liverpool
The Cancer AI Scientist Project
Lennard YW Lee, Gareth Bloomfield + Anthony Hsieh, University of Oxford
MIND-MATTER: AI-Driven Discovery of Self-Learning Materials
Andrey Ustyuzhanin, Constructor Knowledge Labs
AI NanoScientist
Rafa Gómez-Bombarelli + Milad Abolhasani, Lila Sciences
Hermes: A Self-Improving AI Scientist to Discover and Refine DNA Delivery
Henry Lee, Cultivarium
The UK government is backing AI that can run its own lab experiments
MIT Technology Review
By funding a range of projects for a short amount of time, the agency is taking the temperature at the cutting edge to determine how the way science is done is changing, and how fast. What it learns will become the baseline for funding future large-scale projects.