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Field
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performance. However, calculating defect formation energies and migration barriers using first-principles methods remains a major bottleneck in the materials discovery process. To address this, we will develop
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are not limited to): The development of AI-related skills and competencies for project practitioners The factors influencing project managers’ and organizations’ willingness to adopt AI applications
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) techniques developed at UEA to study the interaction of small molecules with Umami receptors overexpressed directly on the surface of live cells (2). You will thus establish ‘rules’ determining which molecular
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relationship between brain structure, myelin distribution and genetic factors in MS. Research Focus: Recently, computational pipelines have been developed to integrate genetic and imaging databases
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portfolio, conducts cutting edge research into the development of future Intelligent Reconfigurable Manufacturing Systems. This is 3-year fully funded studentship and is only open to UK home students. The
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. Applying machine learning to New Zealand’s landslide inventories to model landslide location, character and dynamics. Integrating time-series and inventory data to develop new models to predict location
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, dedicated to generating original knowledge and understanding of air and space power issues. FASI places a priority on identifying, developing and cultivating the next generation of air and space thinkers in
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Research Platform (SARRP) and in vivo imaging to develop image-guided radiotherapy (IGRT) strategies for liver and childhood brain cancers. A key focus of this project is hepatocellular carcinoma (HCC
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and diffusion of gases/vapours. This project will investigate and develop methodologies for understanding the key relationships between fundamental materials properties (degree of crystallinity, extent
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third over the past 25 years, which is inferred from sparse soil data and the widespread decline of their avian predators. Recent developments in soil geophones and contact microphones have enabled