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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the Defence Sector (source: the UK Atomic Weapons
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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short courses in the core subjects of this PhD programme including process intensification and green chemistry. This project is part of the Process Industries: Net Zero (PINZ) Centre for Doctoral training
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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and
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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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School/Faculty: Computer Science Eligibility: UK/International Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780
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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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be awarded a master’s degree in any of the following disciplines: Chemical Engineering, Physics, Mechanical Engineering, Energy Engineering, Environmental Engineering, Computer Science, or other
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software that the candidate will use to study new physics scenarios. The student will join this world leading research programme, performing numerical studies of new strongly coupled field theories taking