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-critical decisions in real time. These systems rely heavily on sensor data (e.g., GPS, pressure transducers, image processors), making them vulnerable to stealthy threats like False Data Injection (FDI) and
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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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experience with maritime systems, radar/sensor fusion, or industry engagement is desirable. What we offer For information about our rewards and benefits please visit https://www.ucl.ac.uk/work-at-ucl/reward
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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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and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing . This is a full time and a fixed-term contract (36 months ) based
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, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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awarded the prestigious Marie Skłodowska-Curie Actions Doctoral Network grant, the AUREUS network is dedicated to addressing the critical global challenge of multidrug-resistant Staphylococcus aureus
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schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing. We provide a wide-ranging benefits
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Hypersonics Doctoral Network. This network is supported by the Ministry of Defence and EPSRC for building the necessary expertise to develop next-generation hypersonic vehicles. Objectives: You will investigate