Topic: robot learning

This half-day workshop debates when explicit predictive models improve robot learning and when end-to-end policies or hybrid systems are preferable. Six debate motions examine generalization, counterfactual reasoning, data efficiency, evaluation, deployment costs and the limits of current benchmarks. Invited talks, contributed spotlights and posters connect theory to empirical comparisons, including negative results. Confirmed speakers include Chelsea Finn, Yunzhu Li, Georgia Chalvatzaki and Vincent Sitzmann. Paper submissions closed on 12 October; camera-ready papers are due on 6 November and

The Soft Robotics Lab seeks postdoctoral researchers working on compliant robotic systems, biohybrid actuators, dexterous manipulation, robot learning or embodied-AI simulation. Researchers will develop and experimentally validate systems, publish findings and co-supervise students. The full-time Zurich appointment starts with a one-year contract, renewable annually. Applications are reviewed as they arrive until 30 November 2026; the start date is negotiable.