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health with the aim of creating healthier spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based
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., temperature, humidity, collision processes) that influence fragmentation. Develop and validate a numerical model to simulate raindrop-freezing fragmentation and its contribution to secondary ice production
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methodology to deliver simulations over a wider operating regime than currently possible. The realisation of this aim involves the advancement of the modelling of the air film and the foil, and their
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to develop a simple and reproducible cell-based model to investigate how the changes in blood flow associated with pre-eclampsia damage the syncytiotrophoblasts leading to the detrimental release of factors
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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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The University of Exeter and Oxford Instruments Plasma Technologies are offering a jointly funded PhD position in computational and machine learning modelling of low temperature plasmas. Oxford
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Trust. The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation
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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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Sustainability Post-COVID-19 Project Supervisors: Professor Rebecca Randell, Dr Joshua Pink Project Description: The COVID-19 pandemic accelerated the drive to home working and acceptance of the distributed
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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