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Field
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still
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methodology to simulate representative offshore operating conditions using a purpose-built prototype system, enabling experimental validation under combined electrical, thermal, mechanical, and environmental
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failure before components are built? We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in
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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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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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real-time fault detection and predictive maintenance strategies. 3. Validation of AI models with real-world SCADA data, ensuring industry relevance. 4. A digital twin framework for safe, simulation-based
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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
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signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health. You will develop and apply cutting-edge techniques in: Signal processing
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computing. Current challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation
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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a