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Field
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experimental and systematic model-based analyses. Scientific publications by the group can be viewed in Publications and artistic outputs . In the Department of Chemical and Metallurgical Engineering , the
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functional motifs are encoded in HS chains and how they influence their biological activity. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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this fundamental challenge, the PhD candidate will be part of a wider team to establish methodological framework, combing utilisation of controlled tree growth test, thermodynamic modelling and advanced optical
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will be required to demonstrate their ability to identify fundamental flow features and model these using suitable CFD methods. Experience in Fortran/C/C++/Python/Matlab is an advantage but not essential
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@ncl.ac.uk To apply, please complete an online application, upload a CV and a cover letter. Your cover letter should be a detailed supporting statement outlining why you are a good fit for the role. Please
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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used to measure motion and deformation. It provides comprehensive full-field deformation data, essential for analysing complex materials, structures and model validation. The DIC community has developed
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the optimization-based methods (doi.org/10.1016/j.apenergy.2020.116152 ), 3- Weakness of the model-predictive-control (MPC) against HESS’s parameters uncertainties, noises, and disturbances (doi.org/10.2514/6.2022