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problems in bioinformatics. This project is part of the Faculty of Science's new Quantum Simulation for Molecular and Material Design (Q-MMD) programme. You will join a growing interdisciplinary team at
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in order to steer the emergent behavior of a collective. The base of the PhD project will be numerical simulations of active systems, where machine learning will be used as a tool to better understand
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will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical modeling, construction of numerical methods, coding, testing, numerical simulations, and
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device structures, and to access the extensive electrical device testing suite available in Bristol, in addition to thermal and electric field analysis of devices, and simulation tools (Silvaco Victory
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most existing fusion codes, SOLEDGE-HDG employs a high-order numerical scheme, allowing the use of meshes independent of magnetic field lines or flux surfaces. This flexibility enables simulations
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of hydrogen storage systems for energy applications. The postdoctoral researcher will contribute to: Development and implementation of advanced multiphysics numerical models Simulation of sorption phenomena and
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inverse problems, as well as the development of numerical methods that can eventually be applied to large-scale wave-imaging problems. The PhD project will have a strong mathematical component. You will
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potential for success as a clinical faculty member. Clinical Assistant Professor • Doctoral degree (DNP, EdD, PhD, or equivalent) from an accredited institution • Master's degree in nursing from an accredited
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characterisation, and numerical modelling to better understand how waste rock properties evolve over time and influence long-term slope performance. This role presents an exciting opportunity to contribute
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principles” is essential for rational materials design, but the underlying numerical simulations are computationally expensive, limiting studies to small systems and short timescales. This project will explore