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opportunities for embedding storage at multiple points within the HVDC architecture—on the AC side, DC side, or directly within converter submodules. The research will tackle several key technical, economic, and
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benchmarks for these architectures. This will also guide hardware design for such devices and tackle crucial challenges in networked systems and entanglement transmission. Candidate’s profile Knowledge
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are essential to meet the demands of next-generation applications. This PhD project offers an exciting opportunity to pioneer separator-free battery architectures using ultrathin, high-performance coatings made
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transport. The acquired insights will guide materials design through collaboration with synthetic partners, enabling a feedback loop that connects molecular architecture to device performance. What we offer
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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Although the development of systems architectures and models has been an established practice for many years, the assessment of the quality of models has relied on expert judgement with
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project will take a comprehensive approach, encompassing the design, manufacturing, and characterisation of metamaterial architectures for advanced radiation detection. The research will involve
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The project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable
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. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport
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candidate will contribute to feasibility studies on hybrid propulsion systems, the development of robust control architectures for autonomous docking, and predictive maintenance strategies using real-time