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nanometre-sized optical structures for intelligent manipulation of light. They require only simplistic (microelectronics-compatible) fabrication processes, and have the potential to replace previous optical
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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embanked, drained and reclaimed for agriculture, but now efforts are being made to restore them through a process called managed realignment. A key feature in the design of managed realignment sites is the
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
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dioxide (SO2) are commonly measured. Each pollutant is produced and destroyed by different processes, and the levels of the various pollutants are correlated with each other, for example, and increase in
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-DED process. Finite element analysis (FEA) is widely used to predict the temperature field during the WA-DED process. Traditional FEA models rely heavily on empirical heat source definitions, such as
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of the mechanisms that lead to defect formation in DED-LB, and improve process control measures to either prevent or mitigate the defects. The additionality of external controls over the laser-matter interactions
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practices for data processing and integration into hydraulic modelling and risk assessment. This project will create a novel methodology for analysing the datasets to achieve meaningful improvements in flood
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a