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Field
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the areas of innovation management, the creation and growth of technology-intensive organisations, business analytics, and entrepreneurship. The research undertaken at the UCL School of Management has been
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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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, or intervention using electronic, mechanical, or smart material systems. This particular PhD studentship, based at the School of Engineering, University of Birmingham, focuses on developing a microfabricated
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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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new. Applicants should have (or expect to obtain by the start date) at least a good 2.1 degree (and preferably a Masters degree) in Engineering or Physical Sciences. Applicants should be able
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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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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