89 algorithm-development "https:" "Simons Foundation" positions at Cranfield University
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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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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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-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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20 Jan 2026 Job Information Organisation/Company Cranfield University Department HR & Development Group Research Field Other Researcher Profile Other Profession Positions Other Positions Application
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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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engagement in the future planning of the University. In return for your time, expertise, and perspectives we can offer you the chance to make a positive impact on the world, to develop your professional
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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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6 Jan 2026 Job Information Organisation/Company Cranfield University Department HR & Development Group Research Field Environmental science Researcher Profile First Stage Researcher (R1) Recognised
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of offers available1Company/InstituteCranfield UniversityCountryUnited KingdomGeofield Contact City Cranfield, Bedford Website http://www.cranfield.ac.uk/ Street HR and Development Postal Code MK43 0AL STATUS
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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