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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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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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Portal or send them to the PGR Admissions team at [email protected] . Please quote the reference: SciEng-DTA Jan 2027-AD-Micro Expression Vision Application link: PhD Computing and Digital Technology
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management of juvenile fish habitats, the student will be trained in a range of inter-disciplinary skills including coastal fish sampling, scientific diving, digital technologies and computer vision. Would
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deep-learning and 3D computer-vision models that detect features while representing a distribution of plausible interpretations. Encode geological relationships in a knowledge graph that stores
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, Edgmond, Shropshire, UK. Project We are seeking a highly motivated PhD candidate to join our research team working at the intersection of robotics, artificial intelligence, and agriculture. The project will
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with Good Documentation Practices (GDP) On the ‘Choosing a programme’ page, please select (Wolfson Sensory, Pain and Regeneration Centre (SPaRC)) Research MPhil/PhD (Full-time). In your application, you
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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further information . Starting in October 2026. You will need to meet the minimum entry requirements for our PhD programme . The successful candidate should hold a degree in neuroscience, cell biology
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply