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Field
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degree in Engineering and have an interest in and/or a good understanding of numerical modelling and testing of structures. Prior knowledge of finite element methods and programming (e.g. C++, Python
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testing dynamic equivalencing methods for power system dynamic simulations and integrating these into commercial simulation tools. Dynamic equivalents are simplified representations of complex power system
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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the preparation of articles for publication in scientific journal(s) Good numerical and statistics skills and familiarity with text editing software, such as Word, Excel, etc. Knowledge of advanced statistical
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research identifies an active and growing research field, with numerous advancements in the past 18 months. A focus on generative AI agents has progressed capabilities towards exploiting zero-day
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is expected to lead to the development of material evaluation methods and a structural monitoring framework to quantitatively assess the quality and robustness of concrete elements in infrastructure
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fields with a socio-technical background Interest in data anonymization and/or technology law will be considered an asset Interest in applying methods commonly used in information systems research (e.g
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equations, and numerical methods. Advanced programming skills in languages such as Python, C++, MATLAB, or R. Strong academic curiosity and enthusiasm for the chosen research area. Application Process To
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, organisational and policy context of the National Health Service. The PhD research will focus on how bottom-up networks are involved in promoting change. In recent years, numerous networks of clinicians
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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so