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aircraft are closely monitored to see if a soot-CCM effect can be predicted. What you would be doing: You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past
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effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions
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deep learning methods to enhance the predictions beyond existing data. By incorporating microstructural features into predictive models, the aim is to create a reliable data-driven modelling framework
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simulation regimes by harnessing and advancing the latest developments in AI Machine Learning. This studentship is a continuation of prior work that is looking at using new cutting-edge deep learning models
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc