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of novel edge-assisted computation offloading strategies that leverages edge intelligence. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core
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ideas from machine learning, econometric choice modelling and mathematical psychology. You will investigate how large language models, optimisation algorithms and automated model search methods can
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-quality and high-impact research and for creating research networks supporting their careers. We welcome applications across all areas in Computer Science, including Algorithms and theory Artificial
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for: Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine
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imaging, medical signal processing, beamforming, image reconstruction, elastography, Doppler imaging, or computational imaging. Demonstrated experience in algorithm development and scientific programming
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networks, edge computing, cloud-native network systems, machine learning. Applicants should have a good understanding of machine learning, optimisation or data-driven algorithm design; strong programming
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expressions for latency and offloading probabilities across edge-only, cloud-only, and edge-cloud computation offloading algorithms. Design and develop robust Python APIs for edge-only, cloud-only, and edge
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potential progression once in post to £48,822 Grade: 7 Full Time, Fixed Term contract up to June 2028 Closing date: 17th September 2026 Background This role is part of the philanthropically funded programme
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The job information is shown below. Please click on the links to see full details. Applications are invited for the position of Research Fellow in Algorithmic Sensing for Music to create a new
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with direct industrial impact. Responsibilities The successful candidate will: Conduct cutting-edge research in Computer Vision, Video Understanding, and Multimodal AI. Design AI models for concept