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Field
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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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to small batches. This PhD will pioneer the transition from laboratory-scale demonstrations to scalable, manufacturable acoustic structuring of polymers, representing a step change in composite processing
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manufacturing processes, especially for the transportation sector and medical technology. To this end, materials are tailored and manufacturing processes are designed to conserve resources – from the modeling
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Start Date: 01/10/2026 Application deadline: 26/03/2026 Applications are invited for a fully-funded Ph.D. studentship in the Department of Aeronautics in structural power composites. This PhD is
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gases. As energetic particles propagate through air, they interact with the air molecules and produce radicals, ions and excited species which can alter the chemical composition of the atmosphere
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
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(DLS) and laser diffraction granulometry, alongside the surface properties of the particles — notably their electrokinetic charge, hydrophobic/hydrophilic balance, and surface chemical composition (FTIR
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of expensive evaluations required for prediction and optimization. A classical approach is co-Kriging (Kennedy--O'Hagan), which models the high-fidelity response through an autoregressive Gaussian process (GP
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responds to climate change in the past and present to improve future predictions of sea-level rise and Earth system feedbacks. The work combines collection of field data, remote sensing, and modelling in