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optimization techniques, coding new algorithms, creating new mathematical theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics
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and has a large group of collaborators. You will be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn More: The Dynamics Research Group
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations, bibliometrics). Conduct data analysis using econometric and statistical
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that handle large network sizes and additional information – such as fine-grained temporal information for email traffic or additional neighbourhood structures – are essential. A key challenge in modelling
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The growing demand for high-performance, low-power large-area CMOS technologies has driven interest in a range of new materials, including silicon-based thin films, organic semiconductors, and metal
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques
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, complexity, and harsh operating conditions. This PhD research addresses two critical challenges in this domain: (1) optimizing sensor movement for inspecting large and complex equipment using robots and
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The School of Computer Science and Electronic Engineering (CSEE) is delighted to announce a fully funded PhD Studentship covering Home fees of (£5,006 for 2025-26) plus stipend. Stipends will match
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microbial communities. In this role, you will develop hybrid species distribution models that combine climate and landscape data to predict how microbial taxa niches shift under changing land use and