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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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nonlinear control and optimisation to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation
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solutions, focusing on integrity assurance for safety-critical applications. It addresses the growing need for cognitive navigation systems that are able to operate reliably with a diversity of dedicated
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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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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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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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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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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