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Field
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process is poorly recorded and needs improvement. Aims and Objectives In collaboration with the Health Innovation Partnership, a modelling pipeline will be devised to cope with the challenges of data
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The project: We invite applications for a fully funded PhD studentship in the Solid Mechanics Group at the University of Bristol to work on the predictive modeling of hydrogen-induced damage in
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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to understand these dynamics. This project proposes a novel pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses
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address Dr Chunwei Xia: c.xia@leeds.ac.uk Co-supervisor’s full name & email address Professor Zheng Wang: z.wang5@leeds.ac.uk Project summary Large Language Models (LLMs) have profoundly transformed the way
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analysis methods. You will gain expertise in integrating experimental total scattering and high-resolution imaging data with artificial intelligence and atomistic simulation tools to overcome current
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Large Language Models (LLMs) are reshaping how we interact with language technologies, yet many questions remain about what these models actually “know” about language. The University of Exeter is
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-material capability with a suitable closure model; (2) improved strategy for interface tracking/capturing; (3) very high-speed scenarios with use of nonlinear Riemann-solvers. If time allows exploratory 3D
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. One useful approach to understanding and enhancing this capacity is through community readiness models—frameworks designed to assess how prepared a community is to address a particular public health