39 computer-algorithm "https:" "Simons Foundation" PhD scholarships at Cranfield University
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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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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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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-terminal antennas and beamforming operating in FR1 bands and future FR-2, enabling robust terrestrial–satellite integration for safety-critical air mobility services. To develop AI-based algorithms
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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algorithms, validated navigation architectures, and new insights into next-generation intelligent mobility solutions. The student will undertake two industry placements at Spirent, use high-tech simulation
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at