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Field
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
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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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transformer designs. Applicants should have, or expect to achieve, first class honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Applicants must
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implementation of decentralised personal data governance frameworks? Technology: How can multimodal knowledge graphs in combination with generative AI help individuals govern their data (e.g. within decentralised
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for candidates with a background in meteorology, climatology, physics, engineering and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world
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and upper stage launch systems. Simulation and test campaigns can be significantly costly in both time and cost having significant implications to technology hardware development. A software that allows
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on a European consortium project, UP2030. UP2030 aims to support cities in driving the transitions
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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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validated physics-informed digital twin FDP approach, developed with industry leaders like AMRC, the project aims to enhance this method and elevate its Technology Readiness Levels (TRLs), supporting
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the field, from tissue scaffold design in tissue engineering evaluation to surgery. The student will focus on establishing best practice for widespread applicability, building on past skin, heart, lung, brain