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the actuator. This involves understanding the physics of the motor, the load it is handling, and the role of the servo-controller in the system. The focus is on managing different fault scenarios efficiently
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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Embarking on a pioneering journey, this project delves into enhancing real-time decision-making in evolving cyber-physical systems (eCPS), crucial in today's modern manufacturing landscape. Focused
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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of water consumption and water pollution. Moreover, only 1% of the materials used in the production process of clothes are recycled back even though around 95% could be recycled. The industry is built
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transformation. As the amount of data increases, it is necessary to store, standardise, process, and make data accessible in a way that gets beyond the quirks of different teams and technology. This requires
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to monitor online the manufacturing process and development of damage in the material and the incorporation of heating and cooling. The Composites and Advanced Materials Centre at Cranfield has recently
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A fully funded PhD studentship in the Centre for Autonomous and Cyber-Physical Systems at Cranfield University. This is a great opportunity to work closely with Thales UK, who are a leading
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An exciting PhD studentship opportunity fully-funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership (DTP). This project would suit students with a
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for this position has a BSc and MSc in environmental sciences, physical geography or biology, knowledge of metagenomic analyses, and a passion for the natural environment. This fully funded studentship is part of