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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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Discipline: Engineering & Technology, Fluid Dynamics, Mechanical Engineering, Other Engineering Research area and project description: Droplets are ubiquitous in nature, industry, and our everyday
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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PhD Studentship: Optimisation of Liquid Metal Filtration and Cleanliness in Nickel Based Superalloys
-supervision by Dr Mark Hardy. The industry aligned EPSRC DigitalMetal CDT offers a four year training programme on integrating data driven with physics-based models of products equipping students with
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engineering related discipline. The project is suitable for Engineering or Physics graduates, with a strong background in Fluid Mechanics, Heat Transfer and preferably with experience in computational modelling
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An opportunity to apply for a funded full-time PhD in the College of Arts, Technology and Environment, UWE Bristol. The studentship will be funded by the Computer Science Research Centre: Ref 2526
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thinking with a data-driven approach to quantify natural capital services and integrate them in infrastructure modelling platforms. These can support actions by stakeholders in the infrastructure systems
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useful life (RUL), is an important part of extending the lifetime of a wind turbine as well as the power that can be generated from it. While both tasks are often driven by experts, public data