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physics proposal for the extension of the Standard Model. The target theory and observables will be identified together with the candidate, depending on their specific skill sets and research interests, and
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characterisation and AI‑assisted modelling. Working within the Composites Research Group, you will develop a digital twin of the PFA cure process, combining mechanistic modelling with neural‑network‑based prediction
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crystallisation. You will build an acoustic patterning system, and fabricate anisotropic composites with tailored thermal, electrical and magnetostrictive properties and link to modelling of these systems
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tools that support the understanding of defect generation during forming. Identify state-of-the-art software and methodologies for modelling composite manufacturing processes and demonstrate how
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. This PhD will address these challenges through a combination of experimental materials science, advanced characterisation and AI‑assisted modelling. Working within the Composites Research Group, you will
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Funding Source: DLA award Eligibility: Available to home fee status and UK domicile EU students We are seeking an enthusiastic PhD candidate to join the Centre for Polymers and Composites (CPC
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the manufacturing process. The embedded optical fibre sensing will be used in conjunction with advanced numerical models for monitoring of composites manufacturing and structural performance. Motivation High
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or constrain compositional cognition, and do the same signatures appear across biological brains and artificial neural networks? This is the central question driving this PhD project, part of the ERC
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publications, participating in conferences). Required skills: • Solid knowledge of heterogeneous catalysis, including the synthesis, physicochemical characterisation and catalytic evaluation of composite
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details Supervisors: Dr Oksana Trushkevych and Prof Tony McNally Research area and project description: Develop scalable acoustic methods to structure advanced polymer composites for lightweight, low‑carbon