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performed well in Domino’s preliminary in-house trials. This copolymer was prepared directly in aqueous media using a technique called polymerisation-induced self-assembly (PISA). Prof. Armes is one
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efficient manufacturing processes that drive significant improvements in production output, cost-effectiveness, and overall industrial performance for our customers. Our projects are collaborative and often
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models? How can machine learning and computer vision models be adapted to accurately classify the different tool wear mechanisms (like abrasion, adhesion, diffusion, and fracture) from high-resolution
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Tailoring the Thermomechanical Properties of High Performance Aerospace & Automotive Composite Materials School of Chemical, Materials and Biological Engineering PhD Research Project Self Funded Dr
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, as part of the collaborative UK Japan civil nuclear research programme . The ideal candidate will have a strong background in cement chemistry and engineering, or a relevant discipline. They will also
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to motivate high performance in others and create high performing teams. Essential Application & Interview Ability to develop creative approaches to problem solving. Ability to analyse and solve problems with
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the EPSRC Doctoral Landscape Award at the University of Sheffield. This project applies breakthrough causal AI to reveal how repairs and maintenance really affect performance—driving smarter, safer decisions
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to translate this technology to clinical use. In this project we will ensure our supply chain, sterilisation and manufacturing methods can be performed to clinical standards at sufficient scale to progress
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. You will benefit from: Access to high-performance computing resources: HPC Stanedge. A comprehensive suite of commercial and open-source software (e.g., Abaqus, Ansys, COMSOL, MATLAB, PyTorch, …). A
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ideal opportunity to join international research programme bridging across disciplines between soil science, analytical chemistry, and geobiology. The post will contribute to the strategic goals