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Field
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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will play an active role in advancing and evolving this technology to expand its capabilities, with a primary focus on developing ligands and tool compounds targeting therapeutically relevant proteins
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. Building upon existing expertise in porous media modelling within the Thermo-Fluids Research Group (UoM), the project will analyse and volume-average these data to develop targeted refinements or propose
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carbon emissions reduction targets set out by the UK- and Irish governments up to 2050, Floating Offshore Wind energy will likely play a significant role. Construction of concrete floaters is attractive
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leadership capabilities. Advances in aero-engine technologies are expected to play a key role in reducing aviation emissions as part of the NetZero targets. This new experimental based research will focus
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are designed to target micropollutants, resulting in the presence of persistent micropollutants in drinking water and treated effluent. Therefore, removing micropollutants from water is imperative along with
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The project: Motivation The development of hydrogen energy technologies is central to the UK government's ten-point plan for a green industrial revolution, targeting a 40% reduction in gas
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refuelling infrastructure for aviation applications. It will directly contribute to the UK’s Jet Zero and Net Zero targets by reducing engineering conservatisms and enabling safer, more efficient use of
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are expected to include: •Robust and “functionally explainable” machine-aided decision support for Safety and Mission Critical objectives e.g. fault detection/tracing, evasive manoeuvring, target selection etc