70 high-performance-computing-postdoc positions at Cranfield University in United Kingdom
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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inspections using autonomous systems. The student will have the opportunity to disseminate work through high-quality peer-reviewed journal publications and presentations at prominent international conferences
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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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will publish high-quality research papers and present their work at international conferences to build global networks with leaders in academia and industry. We invite students interested in joining
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-based solutions (NbS) for water and wastewater treatment. The research will explore sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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. Understanding the process of droplet impact and freezing dynamics at high airspeeds, on textured and non-textured surfaces is critical to deciphering the physics behind ice adhesion and accretion. Previous work
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institutions. State-of-the-art facilities: Access advanced laboratories and high-performance resources. Flexible learning: Tailored research projects aligned to personal interests and career aspirations. Career
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to capture material properties and performance in the context of the disruptor utilisation, To employ integrated computational and experimental optimisation of material and geometrical attributes with respect