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either on theoretical attack construction or single‑system evaluations, rather than on systematic, reproducible, and comparative empirical assessments across classes of AI decision engines. This PhD
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About Us A 3-year PhD-fellowship is available at the School of Biomedical Engineering & Imaging Sciences at King's College London. This position is part of the Cardiovascular Digital Twin network
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its use as a lightweight and strong alternative material remains limited by its relatively low ductility and strength. Paper damage and failure almost always occur in the fiber-fiber bond zones
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to other approved CAPTURE-PH cohorts. You will tackle scanner and protocol heterogeneity, data-quality issues and model failure modes, and establish reproducible multi-centre validation workflows. You will
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, knowledge useful to others beyond those who failed. This PhD project investigates failure in digital ventures: how and why digital startups stagnate and shut down, what their founders learn from
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subsequently other approved cohorts. You will address variation in scanners, acquisition protocols and disease phenotypes; undertake quality control and failure analysis; improve segmentation, feature extraction
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computation is necessary before taking an action. This PhD project will address these challenges by developing trustworthy and resource-adaptive VLA models. A central question is whether an embodied agent can
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structures. The PhD positions Experimental characterization and digital twin development A key challenge in developing a reliable digital twin is accurately characterizing the static and fatigue behaviour
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for outstanding and enthusiastic PhD candidates, with a proven track record of excellence, to work on a challenging PhD project, in an exciting multidisciplinary team. Section Mechanics of Materials The section
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. • Author the process-of-record (flow sheet, recipes, metrology plan, in-line control limits) and support its lab-to-fab transfer to the partner line, including joint failure analysis and corrective process