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debris (Kessler's Syndrome). To manage this, global sensor networks monitor our space environment in both optical and radio regimes. This research project will contribute to advancing space situational
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sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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propellants potentially pose a risk during the proximity operations a kick stage would undertake, for example, condensing on sensitive surfaces such as solar arrays and optical or other sensors
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interaction and origins of mechanical failure under pressure. They should have expertise in microelectrode arrays and multilevel high-density routing for large-area sensor systems. Experience in multicomponent
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Automation (ICRA), ROSCon and others. This PhD offers extensive transferable skills, including expertise in robotics, navigation, sensors, and system design. Graduates will be well-positioned for careers in
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling
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models with a practical experimental platform. FTE: 1 (35 hours/week) Term: Fixed (18 months) The Centre for Ultrasonic Engineering (CUE) group of the Institute for Sensors, Signals and Communications