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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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the application of machine learning and artificial intelligence. By using neural networks developed in Python, the project aims to generate robust and generalisable models for scaffold design. Industrial
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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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group. Advancements in tissue model development are central to the goals of Print4Life, which seeks to revolutionise how functional, bioengineered structures are designed and fabricated. Within
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project will investigate the behaviour and design of rock-socketed anchors through a combination of laboratory experiments and advanced numerical modelling. Laboratory experiments will explore anchor
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evaluating CRN ML models 3. Designing and developing CRN ML architectures for tasks of chemical interest, including reaction property prediction and reaction link prediction. 4. Predicting the properties and
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of nanoparticle-loaded scaffolds; quantify bone healing, osteointegration, and defect closure in critical-size bone models, and establish dose–response relationships for effective scaffold-mediated delivery