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methodologies to study tyre–road contact physics. Providing new insights to better predict tyre–road friction. Based within both the Wolfson School of Mechanical, Electrical & Manufacturing Engineering and the
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control strategies integrating fuel, engine, electric machine, and energy recovery systems for improved overall efficiency. Validate the developed methods through experimental and simulation studies
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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computing. This project is ideal for students with a background in physics, materials science, electrical engineering, or a related discipline. Experience in optics and/or magnetism is desirable but not
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8060F select ‘Electrical and Electronic Engineering PhD (full time)' as
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in decarbonising heat especially in rural, off-gas communities reliant on oil, LPG, and inefficient electric systems. While electrification remains a key pathway, limited grid capacity across
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shift from microwaves to mm-waves (ca. 30 – 300 GHz) or even Terahertz frequencies (ca. 0.3 – 1 THz). Current on-chip interconnect technology relies on printed circuit board (PCB), which is not suitable
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. Successful candidates will have an excellent background in Electronic and Electrical Engineering, Physics or a related subject area (first class degree or equivalent). We invite applications from highly
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project aims to develop state-of-the-art computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the