38 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" PhD positions at Cranfield University
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information into versatile benchmarks supporting development of a new generation of assured PNT systems. Positioning, navigation, and timing (PNT) underpin modern transportation, logistics, and critical
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of novel AM materials on corrosion response of key component and develop a model to predict their behaviour. To address the goals set for tackling international climate change, the power sector needs
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Join us for this exciting self-funded PhD studentship on " Development of Sustainable and Cost-Effective Coatings to Mitigate Battery Thermal Runaway Propagation" in collaboration with
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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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. Focusing on adaptive intelligence, which blends human creativity and machine intelligence, the project will develop Multi-Intelligence Agents (MIAs) to facilitate the seamless integration of social factors
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GNSS alone leaves systems vulnerable to interference, spoofing, or outages, particularly in dense urban environments. The development of 6G networks with integrated TN and NTN infrastructures provides
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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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