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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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limiting their ability to perform essential daily tasks. This interdisciplinary PhD project aims to design a new generation of soft exoskeletons using smart textiles, driven by artificial intelligence (AI
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a
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year. Working at the intersection of water engineering, environmental microbiology, robotics, and lifecycle analysis, you will evaluate autonomous underwater skimming robots that minimise energy use in
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fabrication laboratories. Hands-on experience in surface engineering and scintillator detector testing. Training in modelling and simulation of radiation–matter interactions. Opportunities to present research
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2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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The growing demand for high-performance, low-power large-area CMOS technologies has driven interest in a range of new materials, including silicon-based thin films, organic semiconductors, and metal
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Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing