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justice and inequality in the context of the United Kingdom. As community engagement is central to this research, we particularly encourage applications from candidates with strong existing networks with
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Social Sciences, and the Northern Advanced Research Training Initiative network. The award is available to home and international candidates. If English is not the candidate’s first language, the candidate
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | 16 days ago
communication skills with experience in presenting research, writing study protocols, and drafting strategic papers and manuscripts for publication. Actively build and maintain a network of colleagues and
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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spectroscopy, and gas chromatography. Advice on scientific communication, writing, and data analytics will be provided. Presentation of data at national and international conferences is encouraged and the PGR
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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learning and AI, to interpret complex datasets and extract meaningful patterns related to geographic origin and land-use history. You will join a vibrant research community and benefit from interdisciplinary
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By