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sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
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the integrated framework for high-risk commodities like edible oils, spices, and herbal supplements. The project is jointly funded by UEA and CAMS-UK (Community for Analytical Measurement Science). It will also
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be transferable skills in the technical area of optimisation, industrial exposure, or soft skills including presentation skills, project management, and communication skills. There are also numerous
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to the Net Zero targets. In consultation with the wider CDT community, the work will also include the development of a roadmap for the maturation of the technology and the processes required to have it adopted
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-on experience in environmental management. Interdisciplinary training in hydrogeology, contaminant transport modeling, and decision-making. Networking & knowledge exchange with leading academic and industry
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such as SHACL (Shapes Constraint Language), the NCT3TA reference model, and standards like HISO 100xx and ISO/IEC 11179-xx. Prior experience with these tools is not required—training will be provided
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Modelling post combustion amine CO2 capture plant School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin Hughes
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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of written and spoken English (C1 Level), Collaborative, team-minded and pro-active attitude. High level of written and oral communication skills. Experience with the structures of the University of Vienna
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consider diagnostic waste. The post-holder will be required to demonstrate knowledge of sustainability issues impacting the medical devices industry. They will be expected to work as part of a wider research