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certification, dramatically accelerating innovation cycles. What you will gain: Expertise in Finite Element Analysis, Scientific Machine Learning, Uncertainty Quantification, and Professional Programming
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shaving/shifting, voltage and frequency support, and virtual inertial response. Due to the volatile and intermittent nature of RESs, in this project, machine learning (ML) methods are used to accurately
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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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of reinforcement learning or agent-based systems. LanguagesENGLISHLevelExcellent Research FieldComputer science » Computer systemsYears of Research Experience1 - 4 Additional Information Benefits • Full funding
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Autonomous vehicles (AVs) are advancing rapidly, yet their safety assurance remains limited by the opacity of modern AI systems. Current machine learning–based decision pipelines often function as
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combines flow and materials chemistry, characterisation, and reaction optimisation. You will gain skills in synthetic co-ordination chemistry, advanced characterisation techniques, machine learning and
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develop methodologies (such as acoustic emission method) detecting early signs of damage, leaks, or degradation before they become critical. We will also leverage the latest developments in machine learning
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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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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to also improve and scale the process. We have made major contributions in this area, including the use of Machine learning to discover new cryoprotectants [Nature Communications 2024, 15, 8082