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of experimental modelling challenges and solutions. Advanced programming/data analysis and simulation skills. How to effectively communicate complex and novel research. Opportunities to develop lab demonstration
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specifically for ASD applications, and the creation of high-throughput, miniaturised screening platforms capable of accelerating data generation while reducing waste. The aim is to improve the solubility
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theory, robust and optimal control, and physics-informed modelling, this research aims to bridge the gap between data-driven learning and dependable real-world autonomy. Aim You will have the opportunity
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orla.williams@nottingham.ac.uk for more information Funding support After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process (this will cover
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applications, and the creation of high-throughput, miniaturised screening platforms capable of accelerating data generation while reducing waste. The aim is to improve the solubility, stability, and overall
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-edge adaptive mesh refinement techniques; a lightweight prediction tool developed upon the simulation data to predict key thermofluidic parameters for the design of high heat flux cooling components