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simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with experimental collaborators. The position is part of the Research Council
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where possible validation data will be taken from industrial and openly available literature. The successful candidate will gain experience in computational, analytical and experimental approaches across
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advanced simulation, AI-ready modelling and industrial data to accelerate pharmaceutical manufacturing and the delivery of life-saving medicines? This industrially focused project, co-supervised by
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Studentship Information Supervisor: Dr Hannah Cooper (UoN) Secondary Supervisor: Dr Nicholas Girkin (UoN), Dr Georgina Barratt (BBRO) Subject Area: Sustainable Agriculture and Climate Resilience
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discipline such as statistics, mathematics, computer science, engineering, data science, or a related biomedical/population health subject. Applicants should have strong analytical and programming skills (e.g
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experimental laboratory skills with an interest in working alongside advanced computational and analytical technologies. Experience in interdisciplinary research and collaborative science is highly desirable
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industrial process data Large-scale polymer production systems Operational constraints and engineering decision-making Direct pathways for translation of research into industrial practice The project is
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. The successful candidate will work closely with academic and clinical collaborators to support the collection, management and analysis of multimodal research data. The project will investigate the combined use
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Studentship Information Supervisor: Dr Hannah Cooper (UoN) Secondary Supervisor: Dr Nicholas Girkin (UoN), Dr Georgina Barratt (BBRO) Subject Area: Sustainable Agriculture and Climate Resilience
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in eddy current sensor responses. This will involve both experimental work and analytical interpretation, linking EM signals directly to underlying physical mechanisms. Key research themes include