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This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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academic research training. It would suit candidates interested in careers in academia or industry, especially in AI, sensing, autonomy, robotics, or embedded systems. Background Accurate 3D mapping is
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applications remains an open scientific problem. The Project: This PhD studentship is the computational component of a wider research project to generalise boundary-layer theory to include engineered surfaces
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Research area and project description: AI data centres are digital engines, yet ~30% of energy is wasted as heat in power conversion and distribution. Directly addressing the UK’s Clean Power 2030
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suite of environmental factors are beginning to influence bouquet design, such as embedded carbon, water and biodiversity footprints. In addition, data from consumer feedback is influencing product design
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and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to
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for innovative therapies for atopic dermatitis. The PhD student will be embedded within a vibrant research environment and receive comprehensive training in cutting edge molecular microbiology and biochemistry
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Application deadline: 31/05/2026 Research theme: Catalysis, Synthesis, Chemistry How to apply:uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded and home students are eligible
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embedded system, proving that your theoretical guarantees hold in Rolls-Royce designed hardware implementations. Why Apply? Industrial Impact: Your research directly informs the design of future Rolls-Royce