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of IAI mechanisms and develop innovative antibacterial biomaterials to improve patient outcomes. Structured around three core scientific pillars—regenerative medicine, biomaterial science, and
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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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this fundamental challenge, the PhD candidate will be part of a wider team to establish methodological framework, combing utilisation of controlled tree growth test, thermodynamic modelling and advanced optical
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? Mechanical seals are critical components in high-pressure storage solutions for hydrogen and carbon capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational
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reduction (MAR) algorithms, AI-based segmentation, and automated 3D anatomical modelling, promise clearer, more reliable imaging. Integrated effectively into clinical workflows, these advances have the
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manufacture of demonstrator structures Overall, the PhD student will have the ability to develop advanced skills at the intersection of structural mechanics, manufacturing process dynamics, and uncertainty
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approaches to interpreting these large datasets, as well as computational models that capture low-dimensional structure that reflects the architecture of the neocortex. By working with researchers developing
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids from induced pluripotent stem cells (iPSCs) to create in vitro models for studying
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dynamics of chromatin modifications required for transposon silencing. Project details This project aims to advance our understanding of small RNA-mediated chromatin silencing using advanced genomics and