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Field
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in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
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of mechanical and robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the–loop •Background with relevant
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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changes (so called swelling). Swollen batteries are at risk of rupturing which may significantly shorten their lifetime. Development of advanced computer models is critical for understanding and
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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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, 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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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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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