ai@cam is launching the second edition of its AI Sciencepreneurship Bootcamp, an intensive two-day programme designed to help researchers translate AI-for-science ideas into practical, entrepreneurial ventures. Running from 11–12 February 2026, the bootcamp will support researchers working across scientific domains, offering hands-on training, technical guidance, and access to Cambridge’s wider innovation ecosystem.
Launching the bootcamp, Jess Montgomery, Director of ai@cam, said: “AI is opening new pathways for scientific discovery, but turning those ideas into real-world impact requires targeted support. Our first bootcamp showed just how much potential exists within the University in AI for science entrepreneurship. We look forward to supporting researchers as they develop the technical foundations needed to take their AI innovations beyond the lab.”
The bootcamp builds on the success of last year’s inaugural programme, which supported the development of projects such as Nature Network, an AI-driven tool connecting the public with the natural world; Ötzi, a climate-risk modelling platform for insurance markets; and From Womb to World, an AI-powered digital health tool for IVF and high-risk pregnancies.
This year’s programme will combine technical workshops on foundation models and scientific AI tools delivered by the Accelerate Science team with training in start-up fundamentals from Cambridge Innovation Capital. Participants will also hear from established AI founders and receive structured support to develop and present their ideas at a final showcase with local innovation leaders.
The strongest project emerging from the bootcamp will receive a £3,000 award as part of the final pitch session.
Applications are open to PhD students, postdocs, and early-career researchers working on AI for science across the University of Cambridge and its associated institutions. Researchers must commit to attending both full days of the programme and should submit applications by 17:00 on Wednesday 28 January 2026 via the ai@cam Calls page.
