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Primary supervisor - Prof Kate Kemsley Join us to research and develop advanced analytical methods for tackling food fraud head-on! Economically motivated adulteration of foods is a significant
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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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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, 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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, 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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, 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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further developing both the experimental and data analysis methods that are currently used within the research team. The student will learn how to use the MMI apparatus, gaining knowledge of, for example
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of data-driven approaches within these multi-parameter models to produce faster and more robust correlations and tools that can be incorporated within industrial methods and have an impact on future designs