413 data-"https:"-"https:"-"https:"-"https:"-"UNIVERSITY-OF-RIJEKA" PhD positions in United Kingdom
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this challenge by developing modern data driven tools that help predict and manage corrosion in next generation bio refineries. The project brings together leading researchers from University of Leeds
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London School of Economics and Political Science; | London, England | United Kingdom | about 1 month ago
role in supporting data-driven, policy-relevant research examining energy markets and a range of associated social and environmental challenges. This role is ideal for candidates planning to apply to top
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, maintenance logistics, and weather-related downtime for offshore wind assets. Drawing on climate projections, metocean datasets, and offshore O&M modelling techniques, the research will develop data-informed
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of data. What is needed, therefore, is a test method in which creep strain is developed without changing the cross-sectional area. This PhD proposal seeks to concentrate on the formation of oxide scale and
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interest in the role. For more information or informal enquiries, please contact Dr Shahab Dehghan, shahab.dehghan@newcastle.ac.uk and/or Prof Vladimir Terzija, vladimir.terzija@newcastle.ac.uk . We follow
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and partner urban sites, the successful candidate will collect and analyse real-world environmental data to evaluate how vegetation interacts with the built environment. You will be supported by a
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energy research, combining laboratory experimentation, computational modelling, and data analysis. Experimental work will be carried out in the world class COAST laboratory, examining floating offshore
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, biologging, and coding) to map and analyse complex burrow structures and their usage at our established field-site in South Africa. You will combine this with long-term behavioural and life-history data from
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into its latest Ryzen processors, unlocking new possibilities for on-device AI acceleration. This project aims to maximise the potential of AMD’s cutting-edge hardware for healthcare computer vision
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regulatory obligations. Hydraulic simulators are physically detailed but computationally slow and calibration-intensive, limiting large-scale scenario exploration and optimisation. Purely data-driven