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(UA). This fully funded PhD position offers a unique opportunity to contribute to the future of pandemic resilience through scenario analysis, clinical data collection strategies and implementation
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research with numerical modelling. The group also has a strong track record in data-driven modelling of unsteady flows. This project explores how paired floating vertical-axis wind turbines can enable wind
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that values open science, reproducibility, and career development, and numerous training opportunities in transferable skills For this function, our Brussels Health Campus (Jette) will serve as your home base.
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(i.e. relationally interdependent systems) and encoding nonlinearities in these. The group has plentiful in-house simulation capabilities of numerical models and access to extensive real-world monitoring
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efficient than digital computer and previous experimental implementations. This work is both experimental, numerical and theoretical in nature. You will be selected by the Applied Physics research group
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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plentiful numerical simulations and access to vast real-world monitoring data are available from the outset, your focus will be on the development and critical assessment of the surrogate models, especially