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. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete
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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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that corrected pseudoranges correspond to physically consistent receiver positions across all satellites. Temporal smoothness: enforcing corrections that are consistent with expected receiver dynamics, such as
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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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-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
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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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sub-skills. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How to apply
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discounts, and family-friendly initiatives. Check out the full list on our staff benefits page (opens in a new tab) and use our reward calculator to discover the total value of your pay and benefits
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optomechanics, this project aims to deliver proof-of-concept quantum acceleration sensors ready for technological adoption. [1] Gonzalez-Ballestero et al, Science 374, 6564 (2021) [2] Piotrowski et al, Nature