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to work in an interdisciplinary team are essential. An additional background in physics or experience with practical lab work are advantageous. Interested students are strongly encouraged to contact
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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testing) to understand and tailor the physical and chemical interactions within these complex structures. Cranfield University is internationally renowned for its research into materials for extreme
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
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by the Ada Lovelace Centre and the University of Birmingham. This interdisciplinary project is ideal for candidates with a background in physics, materials science, chemistry, or computational science
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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engagement skills, your interest in the research topic, and future career plans. Full guidance on the application process is available here. Early applications are encouraged. The post is preferred
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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temperature within the engine environment. The aim of the proposed research is to develop modern primary atomisation models which better capture the atomisation physics associated with modern aerospace airblast
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be