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, there is no consensus on the adsorption mechanisms of these molecules on the metallic surfaces. In this PhD project we will use state-of-art molecular simulation methods [2,3] to clarify the adsorption and
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life
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? Mechanical seals are critical components in high-pressure storage solutions for hydrogen and carbon capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational
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areas, and be able to creatively combine disciplines to make new research advances in fluid mechanics. You will be creating data-driven algorithms which can solve state estimation problems in fluid
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their practical deployment. The Project: This PhD will develop the science and engineering required to overcome these bottlenecks, with the following objectives: • Uncover the mechanisms driving enhanced hydrogen
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successful candidate has obtained or is close to obtaining a PhD or equivalent degree in Mathematics, Physics, Engineering, or a clearly related area, with a focus on fluid mechanics. Experience in delivering
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, this project aims to develop a novel modelling and analysis approach to address the mathematical and technical challenges of the fluid-structure interaction (FSI) mechanisms globally. The successful PhD
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may be possible, please contact Dr Mark Whiting once deadline passes. You will need to meet the minimum entry requirements for our Engineering Materials PhD programme. Candidates must meet Surrey
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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 17 days ago
: Analyse how curation and drying impact mechanical properties and hygrothermal performance. Develop a Predictive Model: Create a computational model linking operational variables and material properties