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Field
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and remote sensing analysis could be conducted remotely. Flexibility: Is it possible to do this project part-time? Yes How to apply: Apply online via the above ‘Apply’ button.
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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Several types of polymeric materials undergo rapid degradation under both storage and use, unless antioxidants and stabilisers are added to suppress undesirable reactions. This project is co-funded
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alongside New Zealand’s comprehensive landslide inventories to create innovative models of landslide behaviour. The research will combine field work, empirical modelling, and geospatial analysis, ultimately
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the collaborative interaction of the student and the supervisors who will actively participate in all stages of the project. Input data and training for the use of the code and global sensitivity analysis techniques
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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officially awarded their PhD will be appointed as Research Assistant. Expertise in geospatial data analysis, including remote sensing Expertise in cloud physics, preferably cirrus clouds Aircraft performance
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, where opportunities for collaboration and learning abound. About the role The role involves undertaking high quality research as part of an exciting new internationally funded research project
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About the role Join the Stoneygate Centre for Empathic Healthcare as a Network Meta-Analysis (NMA) Research Assistant. Support ground-breaking research to determine which aspects of empathy training