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Zhongping.Que@brunel.ac.uk for an informal discussion about the project. Eligibility Applicants will have or be expected to receive a minimum 2:1 or 1st class degree in Materials Engineering, or a related
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to: Textile science Textile / garment manufacturing (Bio) Chemistry To apply, please contact the supervisors: Dr Jane Wood - jane.wood-2@manchester.ac.uk and Dr Henninger - claudia.henninger@manchester.ac.uk
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Engineering, Materials Science, Sustainable manufacturing or another related field). The project will require a pragmatic and hands-on approach to problem solving whilst the successful candidate will thrive in
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degree (or equivalent) and/or a relevant postgraduate masters’ qualification (MSc) in materials science, engineering, mechanical Engineering, chemical Engineering, physics, or a related discipline. (E
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leveraging advanced materials science and operando spectroscopy techniques, the research seeks to develop porous catalysts specific for nonthermal plasma catalysis system to improve the energy efficiency
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, civil, and materials engineering. We welcome applicants with a background in: Computer Science Mechanical Engineering Aerospace Engineering Civil Engineering Physics If you have a keen interest in AI
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Undergraduate honours degree or Masters in a discipline relevant to the project. While we expect that this project would suit graduates from a Political Science, Security studies and or International Relations
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-supervised by Dr John Low in the Energy Innovation Centre in the Warwick Manufacturing Group (WMG), and Prof. Richard Walton in the Department of Chemistry (Materials and Analytical Science) in collaboration
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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for the production, storage, and utilization of hydrogen as an energy source. Central to hydrogen-based technologies are the functional materials that facilitate them. Recently, our research teams have identified a