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Field
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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-suited. By the end of the PhD, the candidate will have gained strong skills in experimental mechanics, test management, materials characterization, and numerical modeling, particularly finite element
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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Systems, Energy systems modelling, or a related discipline (upon PhD completion, will transition to Research Associate) In addition for Research Associate PhD awarded in field of Power Systems, Energy
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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wave power without emissions. In the PhD you will have the opportunity to explore and develop novel renewable energy harvesting systems and devise and develop new modelling approaches and conduct
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• You will have experience in experimental design to collect time series data • Evidence of being able to conduct research in the area of medical data analysis or modelling • Demonstrable ability
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with possible supported secondment in company during the study. The student should have a strong interest in mathematical science, software development, data driven modelling, structural mechanics and
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, multidisciplinary PhD research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle
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Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. Offering fully funded, multidisciplinary PhD