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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
such a promising technology, the centralised and resource-intensive nature of current LLMs conflicts with the constraints of aerial 6G networks in terms of limited computation, energy, and communication
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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terahertz (THz) radiation and the collective vibrational modes of biological macromolecules is an emerging field in physical chemistry. Terahertz radiation can be exploited to studying spectroscopic and
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a barrier to bionic vision to date, then develop advanced methods to talk to the brain. Our aim is to utilise this technology to restore sight to those blinded by diseases such as retinitis pigmentosa
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the framework in an industrial testbed and evaluate accuracy and computational performance under realistic load conditions. The student will work closely with Chameleon Technology, the UK market leader in energy
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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Acceptable first degree - Physics, Mathematics, Natural Sciences, Engineering, Computer Sciences. The standard minimum entry requirement is 2:1. Mode of study: Full-time Start date: 1st October 2026 Funding
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strong upper second-class undergraduate degree in Chemistry, Physics, or a related discipline such as Mathematics or Computer Science, are encouraged to apply. The candidate is expected to have a strong
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will also work closely with our industrial partner on process engineering for a scalable prototype facility and product output testing. The successful PhD student will be supervised by Prof Anh Phan from
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep