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Field
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Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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using statistical software. Prepares reports and presentations based on research findings. Collaborates with team members. Contributes to project discussions. Supports administrative tasks related
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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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and develop advanced cryogenic power electronics solutions for key net-zero applications such as all-electric aviation and wind energy. This fully-funded PhD project will provide the opportunity
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software. The TELOS collaboration, co-led by researchers at Swansea University and The University of Edinburgh, and with links in other Institutions in the United Kingdom, Taiwan, Korea, Austria and Japan
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cases. Additional engagement with other organisations may also be part of the research journey, providing exposure to a broad network of practitioners and stakeholders. Funding and Eligibility Fully
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challenging. Characterising the mechanical behaviours of thin foils at elevated temperatures is crucial in defining the load capability of aerostructures during the forming and joining processes. This PhD aims
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analyse large, multidimensional 4D STEM datasets. Develop or adapt software tools (e.g. Python, MATLAB) for image reconstruction, phase mapping, and quantitative analysis of ferroelectric domain wall
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defining the load capability of aerostructures during the forming and joining processes. This PhD aims to characterise the material behaviours of thin sheets and foils (tensile, shear and creep effects