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materials and manufacturing processes, especially for the transportation sector and medical technology. To this end, materials are tailored and manufacturing processes are designed to conserve resources
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
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is funded in association with the Lero Research Centre and the Immersive Software Engineering programme. Faculty: Dr. Roisin Lyons - Kemmy Business School; Prof. Chris Exton – CSIS; Dr. Clare
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cloning). Bacterial production of engineered proteins in E. coli or other microorganisms. Protein purification and characterization via IMAC, SEC, SDS-PAGE, WB, etc. Analysis of bacterial longevity and
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
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addressing the behaviour of thin foil materials for aerospace forming applications. The successful candidate will have a first-class or upper second-class honours degree in mechanical engineering or a related
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science or engineering related discipline. Experience with experimental campaigns would also be desirable. To apply please contact the supervisor: Dr Hannah Mullings, Prof Tim Stallard and Dr Samuel
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first-class or upper second-class honours degree in mechanical engineering or a related subject. This studentship will attract a stipend of £20,480 for four years. The position arises from an engineering
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Mathematics, Technomathematics, Computer Science, Engineering Informatics, Theoretical Computer Science, Physics Description Description The research group Cyber-Physical Systems of Prof. Matthias Althoff