Topic: learning systems

Fully funded doctoral positions combine supervision at ETH Zurich with a Max Planck institute or the ELLIS Institute Tübingen. Fellows have a primary research location and complete a mandatory 12-month exchange at their co-supervisor’s site, earning an ETH doctorate. Research spans machine learning, AI for science, computational biology, neuroinformatics, robotics, control and related learning systems. Applicants need an excellent relevant master’s degree and strong English. All application components, including two or three references, are due by 2 November 2026 at 23:59 CET. Submit the onlin

Max Welling discusses how ideas from physics may inform the next generation of artificial intelligence. The conversation examines physical structure, generative modelling and the relationship between learning systems and scientific discovery.