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Field
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Design of a simulation model for the cutting of metallic and non
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drought early warning and monitoring system for large-scale river basins. The project will explore both data-driven and model-based approaches for drought predictions, paving the way for a continental high
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approach for use with dry fibre forming and RTM manufacturing processes. Assess if a modelling approach can inform process control and optimisation, leading to a reduced part scrap rate. Build simulation
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I specialise in the numerical modelling of high-energy particle collisions , such as those occurring at the Large Hadron Collider. Accordingly, most projects I offer straddle the intersection
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theory, Bayesian inference, Monte Carlo simulation, and statistical analysis of subjective data. Data science and machine learning - big data analytics, surrogate modelling, digital twin development, and
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, and model assumptions, providing confidence bounds on inferred emission rates. Methodologically, the research will combine CFD simulations, surrogate modelling, and inverse techniques to enable
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provide detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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and simulation modeling. A quantitative understanding of ecosystem dynamics provides the foundation for the development of robust management concepts for the sustainable provisioning of diverse
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detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking