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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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This PhD Scholarship is funded by 2022 ARC Discovery Project “Modelling temporal evolution in spatial ecology with dynamical point processes". The world is undergoing rapid environmental change
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modelling of NCLs within industry employs System Codes, which rely heavily on empirical and scale-dependent correlations obtained via experimentation. Unsteady Reynolds-averaged Navier-Stokes (URANS
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reduces computational cost and enables large-scale reactor simulations, current porous approaches, based on Reynolds-averaged Navier-Stokes models, rely on empirical correlations and assumptions that may
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their property. Methodology: The aim is to apply a newly developed Coupled Human And Natural Systems (CHANS) model to simulate and understand the interactive human behaviours and social dynamics before and during
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PhD in Data-Driven Modeling of Homogeneous Catalysts (1.0 FTE) (V25.0035) « Back to the overview Job description Among the most challenging to develop catalytic reactions are stereoselective
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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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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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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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Vacancies PhD Candidate Geospatial Risk Modelling for Climate Finance Key takeaways Effectively understanding and mitigating financial risks associated with climate change is important for