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(subproject A1): This project aims to enhance smartphone-based survey methods as one component of future multi-method travel surveys, to achieve representative samples and travel estimates, to collect
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-enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your
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programming Merits: Experience in modelling erosion problems Understanding of critical state soil mechanics, elasto-plastic and elasto-viscoplastic models Experience in numerical analyses (using finite elements
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and chronic stress, is the most robust risk factor for mood and anxiety disorders but also other psychiatric and medical disorders. In our research we aim to gain a better understanding of the adaptive
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. Methods to be used Fieldwork: participate in one survey to understand the ecosystem and measurement techniques. C++ coding with DuMux source code and its shallow-water module (link Darcy/Richards models
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pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
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complex metal structures. This opportunity is centred around improving manufacturing productivity with advanced laser-matter interactions control and optimisation. The PhD will advance our comprehension
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with microstructural features and failure mechanisms Development of models to describe degradation mechanisms and predict component lifetime Presentation of research findings at project meetings
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upcycling of spent metal oxide cathodes, particularly, high Ni-containing oxides, through chemical-mechanical approaches, ionothermal/molten salt methods, etc. Project 2 (2 PhD students): Direct Recycling
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approaches, including principal component analysis and machine learning, to handle multivariate datasets. Prior experience in data science is not essential; the successful candidate will be supported through