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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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work. A model is to be developed to estimate the material mass breakdown for various cell designs and cell formats. The model will be validated from teardown analysis of commercial lithium-ion battery
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simulations, exploring novel aspects of numerical modelling and expanding the computational mechanics capabilities of the group. This project offers the opportunity to join a vibrant research group and
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Your Job: Analysis of possible applications of CO2 capture and CO2 utilization in the energy system requires detailed techno-economic modelling of these technologies. A major focus of this doctoral
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Vacancies PhD Candidate Geospatial Risk Modelling for Climate Finance Key takeaways Effectively understanding and mitigating financial risks associated with climate change is important for
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study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group Our lab is advancing precision medicine through deep learning models
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team, the PhD student will support the development of discrete choice experiments in two countries, and agent-based modelling, as we plan to model how doctors make job choices among alternative hospitals
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It is imperative to use well characterised, human-relevant in vitro models to assess air pollution exposure impact upon human health, and how it may develop disease. However, despite the known
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, this interdisciplinary project will couple mathematical models of earthworm movement, stochastic models of the measurement process and designed experiments to improve earthworm detection. Project This project will work
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importance, for triggering shallow landslides in sensitive clays. The focus will be on developing computational models that will quantify the mechanisms, precursors and the time to failure. This will be