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and facilitated by the Aminov Family, is available within UCL Great Ormond Street Institute of Child Health. The studentship will commence from 1st February 2026 onwards, under the supervision of Prof
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fundamental methods research to guide in these analytical challenges. In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant
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for additively manufactured switched reluctance machines. The project focuses on optimizing the selection control method according to the machine design. Also, the control method will be used as an input
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Matthew Jones, Prof R Lewis, Prof D Fletcher, Prof David Curtis Application Deadline: 07 November 2025 Details Are you enthusiastic about digital technology and motivated to build tangible change
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will help optimize manufacturing conditions and guide the development of reliable heat treatment strategies. The PhD student will also validate simulation outcomes against experimental results, working
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-to-end virtual supply chains. This project also aims to optimize other thermal processes using digital twins, such as thermally-steered drug delivery processes for applications in oncology. PhD position
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, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains. This project also aims to optimize other thermal processes
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Description The aim of this research is to enhance the durability and fire resistance of veneer-based wood products by developing and optimizing a sustainable wood densification process. The study seeks
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. In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant patient outcomes. You will use a real-world case study on
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the manufacturing process allowing for a faster and more precise optimization trough virtual engineering. You will work within a research team comprising two other researchers dedicated to this project