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project aims to tackle the computational challenges arising in complex system modelling and simulation, by developing new computationally efficient modelling and simulation approaches, able to answer
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complexity required to represent PVD-functionalized electrodes without unnecessarily increasing computational cost. The work will combine fundamental modelling, numerical simulation and experimental
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simulation, especially when combined with knowledge of complex systems, network science, resilience theory, urban science, computational social science, or disruption modelling. About us The candidate will
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Computational modelling of two-dimensional graphene-based materials School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Natalia Martsinovich Application Deadline
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fields. Knowledge: scientific programming, data analysis and processing, artificial intelligence and machine learning, computational modelling and simulation, and fundamentals of physical problem modelling
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and computational modelling. You should have: A PhD (or be close to completion) or equivalent research experience in mathematics, bioengineering, engineering biology, bioinformatics, biotechnology or
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computational modelling in order to understand broader patterns of consumer change over time. We therefore seek to welcome another team member to complement the team and contribute to this goal, with some or
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modelling, resilience indicators, and equity analysis. This doctoral student position is particularly suitable for a candidate who wants to develop strong theoretical and computational expertise while
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mechanistic, spatio-temporal multiscale computational model of the lymph node. You will integrate agent-based modelling with differential equation-based approaches to better understand immune responses
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, and mathematical and computational modelling. Experience with scientific programming, quantitative analysis, or computational modelling, preferably using R, Python, C++, or comparable tools. Interest