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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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on novel nano-structured tungsten alloys for fusion (W-Cr https://doi.org/10.1016/j.apmt.2024.102430 and W-Ti-Fe https://doi.org/10.1016/j.apmt.2021.101014 ). This EngD/PhD project is set within the Fusion
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, qualifications and experience required to perform the role are: Relevant background experience may include urban studies, policy, systems engineering, civil engineering, construction management, climate mitigation
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dynamic team of leading experts in large-area electronics and have access to state-of-the-art facilities within the Henry Royce Institute at the University of Manchester. Applicants should have, or expect
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will dynamically adjust turbine parameters such as yaw, pitch, and torque to maximize Annual Energy Production (AEP) while minimizing component stress. Additionally, a hybrid predictive maintenance model
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well as Civil and Structural Engineering and 27th for Environmental Sciences in the QS World University Rankings by Subject 2025. BEEE is one of the constituent departments of the Faculty of Construction and
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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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. The resulting dataset will be analysed using Structural Equation Modelling (SEM) to quantify the relationships between these factors and uncover both direct and indirect pathways affecting behaviours
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Behavioural Baselines: The research project aims to automatically generate and maintain accurate behavioural baselines for diverse IoT device types within dynamic environments. It will also investigate
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scenarios. By enabling more realistic and dynamic adversarial simulations this project will support the creation of more effective cybersecurity testing, consequently strengthening organisational resilience