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to make decisions, solve problems, and learn. Moving from rule-based systems to agents with strategic flexibility. The range and complexity of tactics, techniques, and procedures that are supported, as
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: Candidates should have a background in one of: engineering, materials science, chemistry, and be willing to learn new disciplines and innovate to achieve the project goals. Additionally, ideal candidates would
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manufacturing and additive manufacturing. Requirements: Candidates should have a background in one of: engineering, materials science, chemistry, and be willing to learn new disciplines and innovate to achieve
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pharmaceutical manufacturing and additive manufacturing. Requirements: Candidates should have a background in one of: engineering, materials science, chemistry, and be willing to learn new disciplines and innovate
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pharmaceutical manufacturing and additive manufacturing. Requirements: Candidates should have a background in one of: engineering, materials science, chemistry, and be willing to learn new disciplines and innovate
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structural alloys. The project will combine advanced phase-field fracture mechanics, continuum-scale chemo-thermo-mechanical modeling, and advanced machine learning techniques for enhanced prediction accuracy
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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at highest risk of kidney function decline, aiding trial prioritisation What you will learn and why it matters This PhD provides a rare skill set sought after in academia, biotech, and healthcare innovation
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decision-making framework to facilitate the design of restoration strategies. In this project, the student will learn on their own time (i.e. self-learning) and under the guidance of the supervisors
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includes over 500m2 of studio space at UWE’s Frenchay Campus. We invite studentship applications from enthusiastic individuals who are strongly motivated to help push the boundaries of machine learning and