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Field
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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Master’s degree in Data Science, Artificial Intelligence, Computational Linguistics, Computer Science. Has excellent academic writing and oral skills in English. Has experience with large language models
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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samples, by the development of advanced computational multiphysics models of stress corrosion cracking and coupling these with process-microstructure models (being developed within MicroAM project). Main
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an exceptional opportunity to conduct cutting-edge research at the intersection of machine learning, healthcare, and computational modelling, contributing to real-world clinical impact. What is offered
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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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
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage