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approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
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training dataset of well-studied volcanoes with known large eruptions, the project will employ statistical and machine learning (ML) methods to identify the strongest predictors of eruption magnitude
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This project fuses machine learning (ML) based inverse design approaches and topology optimisation (TO) to realise multiscale
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About Us The applicant will join the new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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the state-of-the-art wind tunnel facilities of the Department of Aeronautics, and will utilize novel theoretical and machine learning tools. You can expect to become an expert in aerodynamics and turbulent
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the central challenge hindering this vision: the fundamental incompatibility between text-native LLMs and the operational reality of computer networks. Directly applying LLMs is impeded by three core technical
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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these syndromes occur where and when they do? The student will develop statistical and machine learning models to (i) explain the occurrence of extreme fires and (ii) predict their likelihood under present and
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for their employability in applications. Additionally, machine learning methods need to be applicable to high-dimensional and to noisy data that are typically encountered in real-world applications. The aim of this project