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project focuses on developing a mechanistic understanding of coupled redox–dissolution pathways in multi-metal oxide systems and how these pathways can be inferred from real-time process signals. Using
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of battery cells, as well as electrochemical testing and spectroscopic materials analysis (primarily X-ray photoelectron spectroscopy, XPS). The project is carried out in close international collaboration, and
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qualifications Experience in one or more of the following areas is considered a merit: data analysis using ROOT, particle-transport simulations using Monte Carlo codes such as Geant4, FLUKA, or OpenMC, nuclear
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the near future are also encouraged to apply.It will be an advantage, although not a requirement if the candidate has some experience in one or more of the following fields: experience with PFAS analysis
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skills. proficiency in basic IT tools for data analysis, documentation, and scientific writing (e.g., Origin, or similar software) is beneficial. Consideration will also be given to good collaborative
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modelling of flow and transport, analysis of uncertainties in model predictions, and development of efficient methods for evaluating their implications for geological repository safety. The methods will be
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statistical model calibration, machine learning and data analysis. The research environment is international and interdisciplinary, with close links between fundamental method development and technically
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in the presence of strategic, realistically constrained adversaries and probabilistic uncertainty. We seek to develop analysis and design algorithms that incorporate cross-layer information and account