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Field
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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techniques that are useful for the modelling of many real-life systems. These include the development and analysis of stochastic models, computer simulations, differential equations, statistical inference
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physics and diagnostics at the York Plasma Institute Computational combustion modelling using High-Performance Computing (HPC) Machine learning techniques for predictive combustion models Research
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doctoral training programme dedicated to academic research in space propulsion. R2T2 PhD programmes are already underway at nine UK universities, and the programme overall is centred on the Westcott facility
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research programme, titled Collective Action for Race Equity in Health and Social Care (CARE-HSC), aims to address and dismantle structural factors that perpetuate racial discrimination and harassment within
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Autonomous AI-powered red agents for enhanced
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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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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technical expertise in Computational Fluid Dynamics (CFD), simulation methods (including RANS, DNS/ LES), and experimental techniques such as wind tunnel testing and 3D printing. The project will also improve