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for the company, which will open new markets and opportunities. This PhD covers a wide range of skills and so it is essential the candidate has a 1st degree in electronics, computing or aerospace/space technology
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the candidate has a 2:1 or above degree in computing or aerospace/space technology engineering and can demonstrate through other projects or experiences knowledge across the disciplines of software development
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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PhD Studentship: Experimental Investigation of Pharmaceutical Tablet Disintegration and Drug Release
for this PhD position, you must meet the minimum entry requirements for our doctoral programme. We are seeking a highly motivated candidate with: A Master’s degree (or equivalent) in Engineering or a closely
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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Computational Fluid Dynamics (CFD) and Conjugate Heat Transfer (CHT) modelling, which captures both the fluid & solid domains, as required to develop this understanding for engine-representative geometries and
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, including engineering, mathematics and the physical sciences. Students should be able to demonstrate aptitude for computer modelling and enthusiasm to address real-world problems of great policy significance
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(or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject area: Medical imaging, biomedical engineering, computer science & IT
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The School of Computer Science and Electronic Engineering (CSEE) is delighted to announce a fully funded PhD Studentship covering Home fees of (£5,006 for 2025-26) plus stipend. Stipends will match
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funded PhD position is available to evaluate variation in spinal treatments using engineering methods. Specifically, the project will develop and validate novel computational testing methods to evaluate