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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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focus on solid dosage forms and 3D printed drug products. The research will integrate advanced imaging, computational modelling, and pharmaceutical sciences to improve the resolution, reproducibility, and
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will lead the development of novel motor topologies optimised for this cutting-edge material. Supported by experienced supervisors, the student will be able to design, model, and validate working
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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diseases, but is frequently misunderstood, forgotten, and missed. As a toxic proteinopathy that leads to progressive fibrosis, it offers a powerful model for studying common pathways in CKD and represents a
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perfusion as people age with various comorbidities (hypertension, hypotension, obesity) will preserve oxygen supply to the brain. MRI and two photon imaging are used in animal models to understand
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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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transfer and laser-matter interactions. The “design-manufacture-inspect-model-test” approach of this project will equip the successful PhD candidate with a wide range of valuable and transferable skills
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enrichment strategies can be tailored for best conservation success. This PhD project will combine empirical fieldwork with cutting-edge spatio-temporal ecological modelling of systems dynamics to investigate
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noise models, leading to metrics devoid of assumptions about noise impacts (e.g., cross-talk or non-Markovian noise in gate fidelities). As shown by the supervisory team, non-Markovian noise can be a