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Computing Applications and Research (CHEDDAR), we are focused on advancing the integration of UK expertise in communications and networking to maintain the country's leadership in 6G technologies. Our
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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The emergence of edge AI systems—AI deployed on resource-constrained, often battery-powered, devices at the edge of the network—presents critical security challenges. These systems are increasingly
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. This interdisciplinary collaboration with the University of Lincoln and University of Liverpool focuses on developing innovative computational approaches that integrate advanced genomic analysis with state-of-the-art
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the essential criteria for the post, which includes: Have or be about to obtain a PhD in computer science, engineering, mathematics or physical sciences area. Recent high quality research experience in
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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques
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computer science, engineering, mathematics or physical sciences area Recent high quality research experience in machine learning/AI, or both, as evidenced by a strong track record of publications in leading
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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and innovation (R&I) ecosystem. This is a unique opportunity to establish or expand your research programme in the UK, collaborate with world-class researchers, and contribute to national and global
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About us This vacancy sits within the Institute for Sustainable Resources (ISR) within the Bartlett School of Environment, Energy, and Resources in the newly created Centre for Net Zero Market