618 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "ETH Zürich" PhD positions in United Kingdom
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to the delivery of the Chair’s programme. More information on the UNESCO Chair in Storytelling Education for Sustainability can be found here: https://www.lboro.ac.uk/schools/design-creative-arts/unesco-chair
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description In many engineering simulations
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-engineering@kcl.ac.uk Department of Informatics : informatics-pgr@kcl.ac.uk Department of Mathematics : mathematics-pgr@kcl.ac.uk Department of Physics : physics-pgr@kcl.ac.uk Where to apply Website https
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. The Materials for eXtremes (M4X) research group (https://more.bham.ac.uk/M4X/ ) investigates new alloys for extreme environments from fusion & fission reactors, to aerospace gas turbines and concentrated solar
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Digital Citizens, and Robotics and AI which align with the EPSRC Discovery priority of ‘Digital Futures’, and the Mission-Inspired priorities of ‘engineering net zero’, and ‘artificial intelligence
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of ‘engineering net zero’, and ‘artificial intelligence’. This vision is located within RCA’s strategic research priorities of Climate Crisis and the Circular Economy, and Design & AI, as well as the priority
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, realistic configurations and develop a skill set that is highly valued in both academic research and advanced engineering computation. Funding duration – 3 years Where to apply Website https
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Collaborative EPSRC Doctoral Landscape Award Qualification: Doctor of Philosophy in Engineering (PhD) Eligibility: UK Students Award value: Tuition fees and tax-free stipend - See advert for details
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remain available to only a small number of researchers, providing you with a rare and highly valued skill set that aligns strongly with careers in scientific computing and engineering simulation. Funding
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to