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PhD title: Mixed Methods Study of Depression Research Clinics as a means of addressing the primary-secondary care gap in NHS service provision. Principal supervisors: Dr Neil Nixon (School
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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-intrusive alternative to conventional testing methods. However, its performance remains constrained by a reliance on manual configurations, suboptimal test conditions, and limited adaptability to varied
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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delivery or regenerative medicine. The student will formulate new 3D-printable materials and develop new design methods, for functional 4D-printed devices with either fast self-resetting responses or complex
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ultrasound. This project will develop the materials, methods, and designs necessary to 3D-print the next generation of medical micro-robots targeting drug delivery, exploiting combinations of functions
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or temperature. This project will develop the materials, methods, and designs necessary to 3D-print the next generation of electro-responsive soft-actuators. The overall aim is to develop and exploit new designs
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-controlled structural colours that respond to stimuli. You will develop the materials, methods, and designs necessary to 3D-print the next generation of structural colour devices, integrating optically- and
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will develop the materials, methods, and designs necessary to 3D-print never-before created devices. You will develop new functional materials, and new engineering solutions only possible through multi
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging