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Field
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We are looking for a highly motivated and skilled PhD student with expertise in computational hydrodynamics and structural analysis, and a genuine interest in conducting research on hydrofoil craft
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, environmental, energy, and material sciences. In this environment, we are a strongly mathematically oriented research group with a focus on the analysis of various problems in geophysics (in particular
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in an engineering or related subject with experience of mechanics, finite element methods and numerical analysis. Please state your entry requirements plus any necessary or desired background A first
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. Background: Detecting deception is an important but challenging task for numerous organizations worldwide including in the UK (e.g., Probation Service, Police). Whilst there are different approaches, the most
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nonlinear effects. These nonlinear effects will be generalised via correction terms discovered by machine learning from a large numerical simulated dataset. This dataset also allows for extending the theory
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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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operation costs significantly. Besides, there is an opportunity to explore the commercialisation paths of the developed smart sensor prototype. You will gain from the experience in numerous ways, whether it
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deploy these technologies in the industry context without the need for big datasets. You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of
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focus on the formulation, modeling, design, and analysis of future 6G communication networks that are capable of supporting new services for digital ecosystems. Use cases of interest include Security and
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(Co-I) and a post-doctoral researcher focussed on numerical aspects of the network model analysis. Being part of the wider Mathematical Neuroscience research theme within the School of Mathematical