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system will expect to require 25-45GW of within-day energy flexibility, a large proportion of which will need to be delivered by battery EVs. This flexibility can take the form of dynamically changing
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via traditional analytical methods extremely challenging. This project will apply pattern recognition and machine learning techniques to a large database of experimental data to reveal early-stage
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technologies, including: Smart Shop-Floor Connectivity 5G Factory of the Future Big Data Artificial Intelligence (AI) Automation and Robotics for advanced manufacturing systems. Candidates should have strong
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development in modern cements formulated with SCMs is therefore urgently required, to enable quality control and make them practical for use in large-scale construction. This PhD uses advanced spectroscopic
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Low maintenance reliable main bearings for large wind turbines Offshore Wind CDT PhD Research Project Competition Funded UK Students Prof R Dwyer-Joyce, Dr Gary Nicholas, Mr Wooyong Song
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large research portfolio, it has extensive experimental, computational modelling and prototyping facilities. The candidate will benefit from working within a large, multi-disciplinary research group, and
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to handle constraints and optimize the performance or economy of the system. One of the main barriers to adoption of MPC for power system control (and, indeed, large-scale systems in general) is its
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science, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
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Rethinking scholarly and editorial practices for born-digital data Digital Humanities Institute PhD Research Project Self Funded Dr Isabella Magni Application Deadline: Applications accepted all
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in the University of Sheffield’s Centre for International Research on Care Labour and Equalities (CIRCLE). It works in close partnership with a large network of care sector partners and leading