14 image-processing-and-machine-learning Fellowship positions at CRANFIELD UNIVERSITY
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using techniques such as X-ray micro-computed tomography and X-ray Absorption Near Edge Structure (XANES). You will also undertake laboratory-based imaging and develop analytical workflows to process and
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(XANES). You will also undertake laboratory-based imaging and develop analytical workflows to process and interpret complex 2D and 3D datasets. Working closely with the research lead and an
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partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here . The Advanced Vehicle Engineering Centre focuses primarily on the development
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globally. Learn more about Cranfield and our unique impact here . The Advanced Vehicle Engineering Centre focuses primarily on the development, application and evaluation of advanced vehicle technologies
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conferences. About You You will be educated to doctoral level in Remote Sensing, Geography, Geoinformatics, Computer Science, Artificial Intelligence, Machine Learning or a related discipline. You will have
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; cost, carbon or sustainability optimisation; uncertainty and sensitivity analysis; and machine learning or AI-supported optimisation. Strong analytical and programming skills are essential. Relevant
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. The overall project addresses a critical challenge in the UK’s Connected and Automated Mobility (CAM) sector: delivering robust, cost-effective perception systems capable of safe operation in complex, real
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: offshore wind turbines, wave tank experiments, fluid-structure interactions, sensors for offshore structural health monitoring, software development, machine learning and advanced AI modelling, and previous
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involve combining existing models of root system growth, rhizosphere processes and P uptake developed by the project partners and developing new models of the effects and costs of mycorrhizal symbioses
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to lead the delivery of innovative microbiology research exploring how biological processes move carbon into weathered rock and soil parent materials. About the Role This is a Research Fellow role embedded