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Field
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to a wide range of materials, making impactful tools for the scientific community. The models and predictions in the project will be tested against real experimental data and used to drive the design of
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electron microscopy image simulations Development of a machine learning model capable of inferring 3D atomic structure from two-dimensional TEM projection images Application of the new approach
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to an imperfect combustion in engines) and those emitted outside the exhaust (linked to the abrasion of tyres and the wear of brakes). The dynamics of exhaust and non-exhaust pollutants released into the atmosphere
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, and compatibility with existing fuel infrastructure. Co-fuelling of ammonia with hydrogen in internal combustion engines has been extensively studied because of improved combustion characteristics, e.g
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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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, and compatibility with existing fuel infrastructure. Co-fuelling of ammonia with hydrogen in internal combustion engines has been extensively studied because of improved combustion characteristics, e.g
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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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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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high temperature corrosion rate involving mathematical models validated through simulation, experiments and analysis. Gas Turbines are used as a multipurpose power source in various applications like aviation, power
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter