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have a leading programme of research into creating synthetic mimics of IBPs, understanding their function, and deploying them in healthcare and biotechnology - for example storing cells and tissue
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. This project will develop and apply new computational/analytical tools to guide XFEL experiments for specifically tracking lattice fluctuations and ion dynamics in energy materials (batteries). The project will
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, above. Select programme type (Research), 2025/26, Faculty of Engineering and Physical Science, next page select “PhD Engineering (UoSM) (Full time)”. In Section 2 of the application form you should insert
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. While a background in materials science is preferable, it is not a prerequisite, as there are opportunities for retraining. This ensures that the project is accessible to individuals from diverse academic
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apply early for the best opportunity to be considered. How To Apply Apply online by clicking the 'Apply' button, above. Select programme type (Research), 2025/26, Faculty of Engineering and Physical
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Type of award Scholarship Managing department Faculty of Science and Engineering Value The four-year funded A*STAR PhD programme at Manchester enables postgraduate researchers in science and
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Programme: Hybrid CFD and process simulation for process intensification of post-combustion CO2 capture School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof
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The conversion of biomass into value-added platform chemicals can greatly alleviate the reliance on fossil feedstock. Biomass alcohol such as benzyl alcohol is one of the important biomass-derived platform compounds and a significant feedstock, which are used to produce a series of value-added...
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-award PhD programme in a variety of projects across the Faculty of Science and Engineering, with applicants spending four years across Manchester and Bangalore. Students enrolled on the newly launched
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised