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This studentship is open to UK students only The School of Chemistry at the University of Nottingham welcomes PhD applications in Theoretical and Computational Chemistry. The studentship is fully
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system-level visibility. Combined with data-mining methods and embedding techniques, these approaches create opportunities to generate more informed and efficient design solutions. Aim The PhD will focus
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Engineering, or a related discipline with substantial background in fluid mechanics. Essential skills: • Strong knowledge of numerical methods and fluid mechanics • Experience with scientific
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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: Athletes, coaches
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We are looking for an outstanding PhD student with either strong background in computational modelling or significant experience of laboratory work, who is keen to work at the interface between
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travel. Requirements: The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related scientific disciplines. Skills in numerical tools and
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics
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, or computational methods is desirable but not essential. Candidates from non–human factors backgrounds will receive structured training in human factors and experimental methods, while candidates from engineering or
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PhD Studentship: Preclinical modelling and therapeutic targeting of glioblastoma infiltrative margin
(5-ALA)-guided neurosurgery. We now aim to resolve infiltrative margin biology at high resolution using single cell and spatial transcriptomic methods, to identify actionable therapy targets which
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learning, control theory, and embodied autonomous systems. The successful candidate will contribute to the development of learning-based control methods that are not only high-performing, but also safe