15 development-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ETH-Zurich" PhD positions at University of Warwick;
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are developing a suite of models to deliver a through-process microstructural and mechanical property prediction framework for steel. By integrating these models into a cohesive digital twin architecture, the work
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of the project “Human Capital, the Organization of Production and Economic Development” funded by an ERC/UKRI Starting Grant 2023. The project will leverage micro-level data from multiple countries and novel
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development, education, organisational change, and community engagement, reflecting a longstanding belief that drama-based learning cultivates capabilities with value across a wide range of contexts. However
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maintaining accuracy. Although such approaches are widely used, there is still much theoretical development needed to assess the accuracy and efficiency of these approaches. This project therefore seeks
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existing models struggle to capture this complex, multiscale phenomenon efficiently. This project will develop a novel, physics-informed surrogate model using Bayesian machine learning to predict gas
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needs to be balanced with stability and ease of synthesis. Current AI tools can explore vast chemical spaces but often suggest molecules that are unstable or hard to make. This project develops a
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significance. Interdisciplinary Training – Students gain expertise across physics, engineering, computer science, and applied mathematics, developing versatile skills that open doors to both academia and
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, developing versatile skills that open doors to both academia and industry. Collaborative Environment – Work alongside leading researchers and industry partners in a supportive, vibrant community that values
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sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
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), where heat is stored/released through reversible chemical reactions. This project focuses on NaOH water TCES systems, which use cheap, abundant materials [1]. We will develop modelling tools that combine