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Open to: UK fee eligible applicants only Funding providers: EPSRC and LaVision UK Ltd Subject areas: Biomedical Engineering, Experimental Mechanics, Image-Based Measurements, Biomechanics Project start dates: 1 October 2025 (Enrolment open from mid-September) Supervisors: Hari Arora (Biomedical...
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This project aims to enhance best practices in strain quantification for biomedical applications, facilitating the transition of image-based measurement methods from laboratory research to clinical practice. Digital Image Correlation (DIC) is a well-established, non-contact optical technique...
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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device will require an easily operable and user-friendly detection technique to identify targets of interest with minimal training or specialized equipment. The goal is to enable rapid, reliable results
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to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation" (Supervisor: Prof Timothy O'Leary
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T3 (Applications) through reliable quantum advantage assessment. Project Description The project addresses the critical need for reliable, scalable verification and benchmarking schemes in quantum
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fewer moving parts such a structure has, the more reliable it will be. Materials such as carbon fibre composites that are thin enough to be folded or rolled up for storage, but still stiff enough to act
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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, advanced gel polymer electrolytes (GPEs) are needed to boost energy density and reliability. This PhD project offers a unique opportunity to develop cutting-edge GPEs that combine the safety of solid-state
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the models, ensuring usability, reliability, and integration into operational workflows. The successful candidate will benefit from interdisciplinary training in experimental design, advanced speech analysis