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. Quantitative, computational, or mixed-method approaches are particularly encouraged, including but not limited to geospatial analysis, machine learning, predictive modelling, and causal inference techniques
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of the bioprinting process. Objective 2: Training of a deep learning model to predict inputs that will achieve bioprinted scaffolds with the required print fidelity and scaffold micro-architecture. Objective 3
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, little is known about cross-talk mechanisms. In this project, the student will use multi-scale modeling, combining elementary reaction mechanisms with mesoscale and continuum-scale multiphysics simulations
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flow behaviour, droplet formation, freezing dynamics, and ice crystallisation effects, integrating experimental data to refine predictive models for process performance and construct stability. Task 3