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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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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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). Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s energy sector. However, significant technological and cultural barriers are limiting its
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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limiting their ability to perform essential daily tasks. This interdisciplinary PhD project aims to design a new generation of soft exoskeletons using smart textiles, driven by artificial intelligence (AI
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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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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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resilient, long-term cost-benefit case for modernising and protecting our grid. The project will complement the ISS initiative and model data-driven grid optimisation services that ISSs can enable. Firstly