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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on Novel Materials for Stratospheric Aerosol Injection (Dispersal). The post holder will be located in
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Funding for: UK Students Discipline: Engineering & Technology, Electrical and Electronic Engineering, Other Engineering, Physical & Environmental Sciences Qualification: Doctor of Philosophy in
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-mechanical phase-field model incorporating hydrogen diffusion, mechanical degradation, and fracture evolution. - Employ physics-informed neural networks (PINNs) to infer hidden fields and accelerate
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an upper second class (2:1) honours degree, or equivalent in a relevant discipline (Animal Science/Agriculture with Animals Science/Veterinary Bioscience or other Biological Science) or a 2.2 alongside
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communications in smart manufacturing. We are seeking an ambitious and technically capable individual with a strong academic background in Computer Science, Computer Networking, Telecommunications, or a closely
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Area Engineering Location UK Other Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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provider: EPSRC DTP 25/26 Fully Funded Studentship Subject area: Algae biotechnology/computational biology/microbial community networks/ecological theory/evolutionary mechanisms/biomass productivity
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networking with colleagues and students; planning and organising research resources and workshops. Successful applicants will have or be near to completing a PhD in computer science, information engineering