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About the Role Join a multi-disciplinary team that explores human intestinal development and disease using cutting edge single cell and spatial biology technologies, organoid models and
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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and
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science, mechanical engineering or physics. This interdisciplinary project requires a passion for both experimental work and computational modelling, along with a keen interest in learning fracture
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for analysing complex materials, structures and model validation. The DIC community has developed guidelines to ensure robust measurements, continually advancing standards through ongoing challenges. In
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Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art electric motor manufacturing platforms at both locations
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
in machine learning methods for pattern recognition and prediction. An academic or practical background in sleep science and/or elite sport is highly desirable. The candidate will be embedded within
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hub for advanced manufacturing, i.e., Manufacturing Technology Centre (MTC). and with academics from the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute
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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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-fueled engine, power converters, and a battery energy buffer. Key tasks will include developing system-level models, optimising energy management, and coordinating power flow between subsystems to maximise