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previous work to channel flows, both with and without wall roughness. The research will focus on, firstly, optimal synchronisation of minimal unit turbulence (MUT), leveraging the simplified dynamics in MUT
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the optimal values for a range of key parameters and explore how these differ for various turndown ratios and fuel blends. This will be applicable to gas turbine power stations, enabling them to devise
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will focus on three interconnected challenges: 1) Novel Inverse Reinforcement Learning (IRL) for Optimal Stopping Traditional IRL methods are not designed for noisy, trajectory-based optimal stopping
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clinical checks—when interventions can have the greatest impact on patient outcomes. However, in current practice, diagnosis is often delayed until the patient arrives at hospital, by which time the optimal
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cells (hPSCs) are particularly promising, as they can be differentiated into a diverse range of neural cell types. Our lab has successfully optimized protocols for the differentiation of hPSCs
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medicine studies in neurodegeneration. ● Secure peer-reviewed competitive funding for research projects. ● Achieve an optimal standard of academic contribution by publishing research findings in high
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flow, carbon/conduction networks and additive structure of powders to be used in dry electrodes. The development, investigation and optimization of dry, solvent-free manufacturing processes
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of these optimal protocols. Funding Notes This project is for self or externally funded students only. References https://www.quantumbespoke.com/ View DetailsEmail EnquiryApply Online
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design and optimization of hydrogel coating systems. The innovation lies in establishing a closed-loop workflow specifically for interfacial mechanics, with multi-scale integration and physics-informed
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are inherently highly complex. In this research project you will use state of art AI-based optimization algorithms to develop new functionality into industry-relevant digital design tools (CAD) to support