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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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testing) to understand and tailor the physical and chemical interactions within these complex structures. Cranfield University is internationally renowned for its research into materials for extreme
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exploiting the structure of inputs and doing a multivariate complexity analysis. The goal of this project is to develop more efficient parameterized approximation algorithms and preprocessing algorithms (also
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into their structure. However, we don’t yet know how to design these complex printed parts and we are still developing new leading-edge materials to grant them new capabilities. Advantages: In this PhD studentship, you
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mechanical and chemical properties; fully 3D-printed electronics; and devices with mechanical or electrical responses encoded into their structure. However, we don’t yet know how to design these complex
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) structures. The functional importance of this complexity is under explored. Our recent work indicates that different RNA isoforms adopt multiple distinct and functionally relevant structural conformations
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the preferred solution for significant deep waters, their greater technical complexities and economic challenges compared to the fixed-bottom supports provide strong incentives to explore fixed-bottom solutions
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Water, the student will use the Complex Value Optimisation for Resource Recovery (CVORR) methodology to design a practical decision-support tool for identifying, quantifying, and advancing circular
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exhibit complex two-dimensional structures whose performance is governed by subtle variations in layer stacking and nanoscale disorder—features that are difficult to resolve with currently available
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by