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Mobile Edge Computing (MEC) has emerged as a promising computing paradigm to support emerging high-performance applications by deploying resources at the network edge. However, most existing MEC systems are built upon fixed ground infrastructure, such as terrestrial base stations. This...
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rapid, data-driven, physically informed and human-aligned decision framework capable of robust, equity-aware intervention planning under climate uncertainty. This PhD will develop a decision-support
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Funded PhD Studentship in applied geospatial ecology. This project will investigate how dryland vegetation productivity varies across space and time and how it responds to land management. Working
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this industrial PhD studentship in Physics – fully funded by the University of Exeter and Leonardo UK. We’re looking for a student who has a passion for science, with ambition to learn and apply their own ideas
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The experience of pain is dynamic beyond nociceptive signalling, affected by emotional, motivational and cognitive factors. This PhD project aims to investigate the underlying neurobiological
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operational efficiency and sustainability in remanufacturing contexts This funded PhD studentship is open to highly motivated candidates with a strong background in Engineering or a closely related discipline
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from sequential to parallel laser writing, increasing fabrication rates by up to two orders of magnitude. Our vision: We will combine advanced spatio-temporal beam shaping technology developed by Mounaix
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-year PhD position based jointly in the Photonic and Electronic Devices Laboratory led by Dr. Nikolaos Farmakidis within the Department of Engineering at the University of Exeter (Streatham campus, Exeter
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Project Description Chrono-urbanism is an urban planning approach that prioritises time as a core resource, aiming to reduce travel time by placing essential services, leisure, and work within a short walk or bike ride. This approach seeks to create sustainable and healthy cities through “urban...
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machine-learning-based surrogate models to accelerate design and control workflows. This PhD studentship would suit candidates with backgrounds or interests in engineering, physics, applied mathematics