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performance of AI models for fall detection. The research will combine experimental studies on different floor systems, finite element simulations of vibration propagation, and AI-based signal analysis
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productivity and energy efficiency. Bioprocess modelling: Employ simulation, techno-economic analysis (TEA), and life-cycle assessment (LCA) to assess cost and GHG performance. Candidate’s Competencies and
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product quality, reducing waste, and enabling sustainable, low-carbon manufacturing of high-value materials. Academically, the work will contribute to the growing field of multiphase flow modelling. Contact
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of the following: numerical methods, high-performance computing (HPC), Computational Fluid Dynamics (CFD), applied mathematics, physics, engineering or subsurface flow modelling. Enthusiasm
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we place value on prior experience, enthusiasm for research, and the ability to think and work independently. Excellent Analytical skills and strong verbal and written communication skills are also
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standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently. Excellent Analytical skills and strong verbal and written communication
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, and the ability to think and work independently. A master’s degree is not required if you hold a 2:1 or can demonstrate equivalent experience through work or research-based projects. Essential
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UKRI rate). Additional project costs will also be provided. Overview The demands of energy-efficient and high-performance photonic devices have been driven by the quantum revolution. This PhD studentship
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-efficient and high-performance photonic devices have been driven by the quantum revolution. This PhD studentship aims to develop novel materials and components that facilitate strong light-matter interactions
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at the 2026/27 UKRI rate) (note that the 2025/26 rate is £20,780), and a research training support grant of £20,000. Overview This PhD project is part of the EPSRC Centre for Doctoral Training in Process