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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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actuation, feedback and computation across their soft bodies, blurring the boundary between material and machine. Our work hints that key platforms to capture such material intelligence are ‘robotic materials
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and algorithmic framework to assess and improve the resilience of FL-enabled autonomous systems under such heterogeneity, explicitly incorporating the human in the loop. The project will draw
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The University of Exeter’s Department of Computer Science invites applications for a funded PhD studentship to commence on 21 September 2026, or as soon as possible thereafter. For eligible students
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upon the candidate completing 70 hours of teaching per year during the initial 3 years. The pan-University Graduate School offers an integrated training programme to the postgraduate community within a
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entry requirements . Candidates must have a strong motivation for research and excellent programming skills. Expertise in developing computer vision and machine learning algorithms would be desirable
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will develop nanoscale devices which use magnons (collective excitations in magnetic order) as information carriers for ultra-efficient, compact, brain-inspired computing. This project is positioned
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intelligent and resilient navigation systems, contributing to the UK’s Net Zero transport strategy. Outcomes will include novel AI algorithms, validated navigation architectures, and new insights into next
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simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with experimental collaborators. The position is part of the Research Council
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Location: Faculty of Science and Faculty of Engineering, University of Nottingham, UK Start Date: 1 October 2026 This PhD offers an exciting opportunity to explore reservoir computing, a new