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Field
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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in radiation–matter interactions, computational modelling, and materials science, with a strong publication record (h-index 36, i10-index 69). Dr Francesco Fanicchia, Research Area Lead: Material
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PhD Studentship: Microswimmers with Autonomous Propulsion Inspired by Biology and Designed with Physics Are you fascinated by working at the intersection of physics and synthetic biology? This PhD
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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the Defence Sector (source: the UK Atomic Weapons
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with Professors Serena Best and Ruth Cameron at the Cambridge Centre for Medical Materials in the Department of Materials Science and Metallurgy. The SHIELD Doctoral Network offers an exciting
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second class UK honours degree or equivalent in Engineering, Chemistry, Applied Physics, or a related discipline; a Master’s degree in these subjects would be of advantage. Funding This is a Fully-funded
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-time Entry requirements The standard minimum entry requirement is 2:1 (Hons) in physics, chemistry, natural sciences, mathematics, computing, environmental sciences, or similar numerical subject. Start
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-subsaturated air (but where no contrail was formed). Research Associate: Hold a PhD in Aerospace Engineering, Atmospheric Science, Physics, or a closely related discipline*, or equivalent research, industrial
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new sustainable femtosecond laser nanomanufacturing process to overcome the challenges of atomic sale precision, feature size and defects rates for quantum dots. In this project, molecular dynamics
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skills. Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug