AI Scientist: Funded projects

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.