We are seeking exceptional candidates for a full-time Postdoctoral Research Assistant to join the Applied Artificial Intelligence Lab (A2I) at the Oxford Robotics Institute in the Department of Engineering Science. The post is funded by EPSRC and is fixed term to the 31st January 2027. A2I explores core challenges in AI and machine learning to enable robots to robustly and effectively operate in complex, real-world environments. A key focus area of the group is to advance research in representation learning for scene understanding and prediction as well as task and motion planning in order to enable robots to perform a broad array of bespoke tasks effectively and with minimum operator intervention. This role is an integral part of our EPSRC Programme Grant in Embodied Intelligence and will involve both theoretical and practical work in the context of real-world robot learning. The successful candidate will advance the state-of-the-art in machine learning and robotics with a particular research focus on developing the theoretical and algorithmic foundations of compositional world models. A key application focus of the grant lies in rapid and safe real-world skill acquisition in application domains such as collaborative manufacturing and the circular economy. You should possess a Ph.D. in machine learning, robotics or a closely related field with a focus on compositional world models. Further, essential are a strong publication record in the primary field of research and familiarity with the existing literature and research in the field. Experience in reinforcement learning and / or task and motion planning are desirable, as is a proven track record of deploying machine learning models on real-world robot platforms. Informal enquiries may be addressed to Prof. Ingmar Posner (email: ingmar@robots.ox.ac.uk) For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ Only applications received before midday on the 5th December 2025 can be considered. You will be required to upload a covering letter/supporting statement, (describing how past experience fit with the advertised position), CV and the details of two referees as part of your online application.