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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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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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that by combining electrospray deposition (ESD) with scanning tunnelling microscopy (STM) it is possible to deposit intact conjugated polymers in ultrahigh vacuum (UHV) and to acquire unprecedented sub
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association of candidate genes with these surfaces. The project offers a unique opportunity to acquire a broad skill set of biochemical, biophysical, bioimaging and molecular techniques while working with a
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unique opportunity to acquire a very broad skill set of biochemical, biophysical, bioimaging and molecular techniques, combined with diverse data analysis and bioinformatics skills. The project would suit
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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Entry Requirements - Swansea University Knowledge in biology is not essential, but the candidate will be required to learn appropriate biological and clinical knowledge in order to develop mathematical
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, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify
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factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised