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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | about 2 months ago
: Analyse how curation and drying impact mechanical properties and hygrothermal performance. Develop a Predictive Model: Create a computational model linking operational variables and material properties
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limits map which describes the performance of a turbine wheel with respect to the microstructure through simulation and empirical testing. The aim of the project is to develop a modelling and simulation
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, increasing costs and resource waste. This Ph.D. project aims to address these challenges by advancing fault diagnosis and prognosis (FDP) for complex mechatronic systems. Building on Supervisor Team's
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour of polycrystalline metals. The post holder will be located in Central Cambridge, Cambridgeshire,...
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; Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | 3 months ago
the complex way in which the prevalence or odds (e.g., of childhood stunting) differs according to the combination of many variables/dimensions of inequity uniquely in different countries. The Multilevel
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approaches (e.g. SPG) as well as the use of machine learning, advanced computing, statistical modelling to explore the stochastic response to complex scenarios. This project offers the opportunity to undertake
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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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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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and prosthetic devices in the real-world. This PhD project offers the opportunity to work on pioneering research that combines state of the art computational modelling (deep neural networks) and
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Research theme: Materials 4.0 No. of positions: 1 Open to: UK applicants This 3.5-year project is funded by the School of Natural Sciences and is available for home students; the successful candidate will receive an annual tax free stipend set at the UKRI rate (£20,780 for 2025/26). Tuition fees...