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probability, allow for the application of tools from probability theory to combinatorial problems and motivate the study of the typical properties of various combinatorial models, such as the Erdős–Rényi random
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to address these combinatorial decision challenges, with a specific focus on nanocellulose production in the UK. By exploring different feedstock options, supply chain configurations, and process pathways
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tumours and metastases with the goal to design combinatorial therapeutic approaches. The project will involve the use of genetically complex organoid-derived transplantation mouse models of pancreatic
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chemistry of polyol binders (HTPB) and isocyanates for optimization of formulation (pot life) and product mechanical properties for application in solid rocket propellants. Due to the confidential and
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assembly of foldamers often lack the mechanical properties required for their optimal performance as biomedical devices. Polymers have recently emerged as a promising class of materials for biomedical
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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Optimizing Routes in Unpredictable Environments Robotics Research Group Adaptive and Continual Learning for Socially Intelligent Robots Designing Evolutionary Games for Therapeutic Interaction End-user
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development of optimal passive mitigation solutions through the enhancement of components such as elastomers. These elements will be selected and optimised to absorb and isolate shock and vibration while
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methods to improve systems, and ML research develops such methods. Major gains are made when the development of ML and systems are symbiotic and co-optimized. This is relevant across a broad spectrum of
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particular, we will use topology and shape optimisation methods to compute the optimal domain shapes that can stabilise solutions with desired/prescribed properties. We will use methods from inverse problems