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and advancement of multi-fidelity finite element models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual
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learn and grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Dr Yingzhen Li ( https://yingzhenli.net ) and her
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: Development and advancement of multi-fidelity finite element models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using
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enabling process monitoring, learning, and policy training while ensuring safety and efficiency. For this, we develop novel learning-based control methods with practical applicability and theoretical
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, excision, filtering, estimation, and mitigation methods; and quantify effects on radar data quality, including reflectivity, radial velocity, spectrum width, and dual-polarization variables. The work
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codes exists, what architectures do they need, how can computing be done on them - Developing software for efficient comparisons and resource estimation - Exploratory research in novel computing
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will initially use established datasets and simulation environments to enable controlled comparison with existing approaches. Selected methods can then be evaluated through real-world human-robot
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, our actions together, large and small, contribute to a better world. We look forward to receiving your application! Work assignments You will join the research project Countering Bias in AI Methods in
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engineering schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Engineer in Structural/Finite Element Analysis for Maritime Drone
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field robotics and tests its methods on robots in real environments. We are now looking for a postdoctoral researcher to develop sensing and autonomy for drones that inspect infrastructure and terrain in