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confined battery geometries. Advanced modelling—including computational fluid dynamics (CFD) and transient thermal analysis—is required to accurately capture heat flux distributions, temperature uniformity
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for many developments in model theory, starting with strong minimality, as well as providing some of the most important applications where model-theoretic tools are applied to algebraic geometry. After
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to eruptive activity. These transitions pose significant challenges to hazard management (1). Physical parameters, such as the location, geometry, and size of the volcanic system, and their changes over time
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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on such jets — although their detailed properties remain unexplored. In this project, we will develop new computational methods to compute and characterize these novel wave solutions, with particular emphasis
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, and edge computing, AASs are evolving into smart, interconnected solutions for addressing the dynamic challenges of modern cities. This project investigates how to coordinate these multifunctional
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programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
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Project Supervisor - Professor Rudy Lapeer The Birth4Cast “Digital Twin” aims to create a subject-specific computational biomechanics simulator of childbirth from prenatal fetal MRI scans
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community, supported by cutting-edge research facilities and excellent training opportunities. The Norwich Research Park Biosciences Doctoral Training Programme (NRPDTP) is offering fully funded studentships
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across different imaging devices, including future sensors with unknown spectral sensitivities. Training The student will be based at the Colour & Imaging Lab at the School of Computing Sciences which has