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together knowledge in fields as diverse as, e.g., mathematical logic, the theory of computation, software engineering, artificial intelligence, data science, global and local history, classical philosophy
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foundational computer science and mathematical foundations of AI; and experts in the industrial utilisation of emerging AI technologies for various manufacturing and built environment inspection processes
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or second-class honours degree in engineering, physics, mathematics, computer vision, or a related field. Interest or experience in computational modelling or coding—beneficial but not required. A
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, mathematics or related field. Experience with computer programming languages (e.g., MatLab, Phyton), familiarity with geographic information systems and systems thinking methodologies and an interest in
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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& Environmental Science Mathematics & Statistics Project description Offshore wind is a core component of global solutions to net-zero. The increasing demand for renewable energy is driving the installation
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models that are of relevance to understanding potential future changes in the subpolar gyre of the North Atlantic. The ideal candidate will have a strong background in mathematical and statistical methods
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Honours degree and a Masters, or a Distinction at Masters level a degree (or the international equivalents) in physics, engineering, mathematics or environmental/earth science and have studied fluid
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, mathematics or related field. Experience with computer programming languages (e.g., MatLab, Phyton), familiarity with geographic information systems and systems thinking methodologies and an interest in
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(or equivalent) in a numerate discipline, preferably in mathematical, computational, biological, engineering or physical sciences subjects or a related discipline, with an interest in using technology to solve