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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
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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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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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metascintillator prototypes towards clinical application. The research will combine experimental surface engineering, advanced materials characterisation (SEM, XRD, spectroscopy), and performance testing alongside
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The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship fully-funded by the University of Exeter and National Grid to commence on 01 July 2025 or as soon
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the Department of Computer Science and Technology at the University of Cambridge. The position will be for 12 months from the 2nd February 2026 in the first instance. Project research topics must fall under
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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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, and materials science, with a strong publication record (h-index 36, i10-index 69). The second supervisor is Dr. Indrat Aria, a materials scientist with expertise in low-dimensional nanomaterials and
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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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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from