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applications in both conventional and renewable offshore energy. Objectives To reduce computational time during the training process, a linear solution based on potential flow theory is used as the training
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embedded into cyber‑physical systems (CPS) such as autonomous vehicles, smart grids, industrial control systems, robotics, healthcare devices, and intelligent transport infrastructure. While significant
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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Phd Studentship in Computer Science: Empirical Security Assessment of AI Decision Engines in Cyber-Physical Systems Award Summary 100% home fees covered, and a minimum tax-free annual living
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of blades to discs using solid-state joining is a key factor in achieving cost-effective, high performance and low-weight fan and compressor stages in aero-engines. LFW is an established joining process
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21 Sep 2026 Job Information Organisation/Company Imperial College London Department Department of Physics Research Field Physics » Optics Researcher Profile First Stage Researcher (R1) Positions PhD
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-year Computational Project to use state-of-the-art Computational Chemistry techniques to understand structure-property relationships in thermal batteries, and to derive new understanding to guide design
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of blades to discs using solid-state joining is a key factor in achieving cost-effective, high performance and low-weight fan and compressor stages in aero-engines. LFW is an established joining process
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direct continuation of that programme. The project will develop hybrid QD–Rb interfaces for frequency conversion and subsequent storage of single photons in warm rubidium vapour. High-quality epitaxial III