39 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD scholarships at Cranfield University
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usability and accuracy, as well as conducting field tests to validate their effectiveness. Additionally, the research will explore the economic viability of these sensors to enhance real-time data collection
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training will be provided. We particularly welcome applicants who are excited about integrating ecological understanding with data-driven methods. There is flexibility to tailor the research to your
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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reliability and maintenance strategies. Filter Rig: An experimental setup to study filter clogging phenomena, allowing for the collection of data to develop and validate prognostic models for filter
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mitigating jamming and spoofing threats in real-time. Integration of Trusted Execution Environments (TEEs): Investigate the use of TEEs to create secure zones within embedded systems, facilitating secure data
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establishing events and aiding future design improvements. Currently, there remains a paucity of data in this domain, making it difficult to identify any notable trends and associated failure mechanisms
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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for this research studentship, please complete the online application form. For further information contact us today: T: +44 (0)1234 758540 E: study@cranfield.ac.uk
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for the collection of data to develop and validate prognostic models for filter degradation. Integrated Drive Generator (IDG) Rig: Simulates the operation of an aircraft's IDG, used to investigate fault detection
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to enhance real-time data collection and improve monitoring practices, and the social factors that influence their uptake. This studentship offers a unique opportunity to engage in groundbreaking research with