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advanced actuators, smart materials, sensor systems, and new adaptive control methods to manage the open-ended degrees of freedom of morphing systems. Methods will span both active smart-material based
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expertise in analysing and interpreting satellite remote sensing data from Synthetic Aperture Radar (SAR) and multi/hyper-spectral sensors for measuring ground deformation, mapping surface changes due
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DC-DC converters, AC motor drives, and control algorithms Sensors such as MEMs accelerometers, piezoelectric sensing, MEMs microphones, etc. Your working location can be hybrid on-site/work from home
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a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, becoming a key component for managing smart cities. Except for a few applications, DAS data are typically
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algorithms for dynamic structured data, with a particular focus on time sequences of graphs, graph signals, and time sequences on groups and manifolds. Special emphasis will be placed on non-parametric
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and simple embedding alignment to develop architectures that can process and reason across modalities (vision, language, audio, sensor data) from the ground up. How do we build a truly unified
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contribute to research and development efforts focused on creating accurate digital twins, improving anomaly detection models, and integrating visual data with spatial sensors like RGBD and LiDAR. This role
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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planning algorithms to real hardware to simulate multibody 0g space dynamics. Candidates with demonstrated experience with robotic algorithms and writing software for robotic hardware will be prioritized
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have designed and introduced new control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the