AI. Climate change. Two defining challenges. One shared future. How will they transform our world, and how can we shape what comes next?
Join an eight-week interdisciplinary programme on either AI or Climate to explore society’s most pressing challenges through inspiring lectures, practical skills and hands-on projects.
It's the Week 5 Student Bulletin!
We're now over halfway through term – is it too early to start the countdown to Christmas?
Noah has sent us a lovely photo of his two furry friends: Algebra (the grey one) and Trigonometry, or "Trig" for short (the black-and-white one), enjoying the sun and getting a nice tan. How adorable! 🐾
We are currently inviting applications for two Postdoctoral Research Associate positions to work with Professors Jon Keating and James Maynard at the Mathematical Institute, University of Oxford. These are three-year, fixed-term positions, supported by a Simons Collaboration grant funded the Simons Foundation that commences in January 2027. The starting date of the positions is flexible, between January 2027 and October 2027.
Kate Wenqi Zhu is a Postdoctoral Researcher at the Mathematical Institute, University of Oxford, who will give a talk on the topic of ‘AI for Mathematics: open problems, a workflow, and what it leaves behind’.
2026 has felt like a grokking moment for AI and mathematics. This talk is a working report from a numerical analyst, not an AI evangelist. I will describe (1) seven open problems from the numerical linear algebra catalogue that we resolved with AI agents, and how the community has responded; (2) the agent-to-agent workflow behind them, designed so that every proof is interpretable, traceable to its sources, and teachable, with independent cross-model review before anything is recorded as a result; (3) two worked examples: a deterministic eigenvalue-separation result whose proof pieces together convex analysis and classical numerical linear algebra, and a sum-of-squares result whose key idea we distilled into a reusable 'skill' for later problems; and (4) what I think this means for mathematicians: which problems suit AI, which suit people, and why asking the right question matters more than ever. I would like to leave time for an open discussion.