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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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-heavy model updates, the proposed approach will use event-driven and sparse-update mechanisms so that learning updates are transmitted only when meaningful local changes occur. This will significantly
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. Quantitative, computational, or mixed-method approaches are particularly encouraged, including but not limited to geospatial analysis, machine learning, predictive modelling, and causal inference techniques
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. There will be a requirement to teach in undergraduate laboratories and tutorials as part of the scholarship. Tasks: The successful candidate will be involved in: 1. Applying first-principles and machine
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the application of machine learning and artificial intelligence. By using neural networks developed in Python, the project aims to generate robust and generalisable models for scaffold design. Industrial