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, antennas, and electromagnetic metasurfaces. The computer-aided simulation of electromagnetic fields is critical in the design of most computing and communications devices, such as high-speed interconnects in
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- skills – experience: analytical skills, ability to demonstrate good knowledge in system modelling – simulation, (classical or modern) control theories or control applications with evidence Desirable
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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2:1 in BSc Chemistry or an MSc in any applied chemistry degree, including inorganic chemistry, chemical physics, analytical methods, simulation and modelling of chemical reactions. English language
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations
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., extracted from the collected data) and “predications” (generated by the C2 operational model). The tool will detect subtle discrepancies indicative of stealthy data manipulation with zero false alarms
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services. The PhD will explore innovative workforce models and system-level changes that can improve recruitment, retention, and staff wellbeing in healthcare settings such as general practice, ambulance
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manufacturing (3D printing) techniques. The purpose of the studentship is to develop a next-generation in vitro model of aged human skin to evaluate the cytocompatibility of materials used in maxillofacial
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity