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, flexibility becomes an essential feature, driven by the development of flexible components and open networks. Development of Digital Twins, capable of building dynamic models from information gathered form live
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the predictions of opaque models that are widely deployed in high-stakes decision making scenarios. Of particular interest to this project are example-based explanation methods that use individual data points
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-scale view of online interpersonal relations, enabling a more nuanced investigation of biases in information diffusion, polarization, and echo chamber effects. To harness this information, novel models
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evaluation of their efficacy to mitigate the negative impacts of T2DM on osteoprogenitors. The PhD candidate will establish and validate an in vitro model, screen new therapeutics using that model, then
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for structural variants and copy number variants (SVs/CNVs), will be used to optimize data analysis and variant discovery. The project will focus on identifying previously overlooked pathogenic variants, exploring
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numerical models of each system in terms of heat transfer and groundwater flow. These calibrated models will be then used to evaluate potential optimised system configurations to gain more heat from the same
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this project, using extensive primary cell culture, molecular analysis, scRNAseq, non-invasive imaging analysis, along with mechanistic studies using 2D/3D culture models, we will dissect the distinct cellular
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social sciences, statistics, or equivalent). The study provides training in applying advanced statistical methods (such as Structural Equation Modelling, Latent Class Analysis and/or Multi-level Modelling