27 parallel-computing-numerical-methods PhD scholarships at University of Nottingham in United Kingdom
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candidates with: ◾First or upper-second class degree in Robotics/Computer Science/Cybernetics/Mechatronics/Mechanical or related scientific discipline ◾First rate analytical and numerical skills, with a well
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are seeking talented candidates with: First or upper second-class degree in Robotics/Mechanical/Cybernetics/Mechatronics /Computer Science or related scientific discipline. First-rate analytical and numerical
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to characterise the material behaviours of thin sheets and foils (tensile, shear and creep effects) to improve the forming process and optimise process variables. Experimental methods for testing mechanical
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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approx. £15-17k across full PhD programme). Monthly stipend based on £20,780 per annum, pro rata, tax free. Working hours: Full-time (minimum 37.5 hrs per week). Working style: Primarily in-person at host
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Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives for aviation use
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training and mentoring programme in place that consists of both key skills training and online monitoring of research progress. Project Options: Option 1 - A multi-omics spatial approach to characterise and