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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive
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discovery process, leading to more economic and effective drugs that can significantly improve the health and lifestyle of millions. The resulting methods are also expected to have an impact in materials
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-B4 Investigators: Prof. Dr. Meng Wang, Chair of Traffic Process Automation , and co-supervised by another expert in traffic control Requirements: excellent or very good university degree
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experimental research in nanoparticle catalysis using advanced operando electron microscopy This collaborative PhD project between Technical University of Munich (TUM) ( the group of Prof. Barbara A.J. Lechner
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supervisor Prof. Dr. Oliver Heiri and the Geoecology group. The research should contribute to methodological and interpretational advancements in the field of chironomid palaeoecology by applying new methods
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs
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an Ahpra-registered pharmacist or holds qualification eligible for registration with Ahpra Application process Future and current student, please contact us via the EOI form . Enrolment Requirements
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subsequent precipitation hardening process. In addition, promoting a circular economy in the aluminium industry by increasing recyclability and using more recycled aluminium is essential for saving resources
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larger effort to map material performance limits and unlock untapped robustness in engineering alloys. You will: Develop and implement physics-based microstructural models to simulate damage and fatigue
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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