352 postdoctoral-soil-structure-interaction-fem-dynamics PhD positions in United Kingdom
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This PhD project aims to develop and apply innovative photogrammetry-based analytical tools to enhance the spatial and structural characterisation of pharmaceutically relevant materials, with a
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the areas of fluid dynamics, turbulence and net-zero combustion. There is substantial scope for the student to direct the project with the main focus on (i) Generating an advanced Direct Numerical Simulation
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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Council The new gallery will provide a home for the public programme, serving as a testing ground for innovative curatorial research and community involvement. Working closely with a supervisory team, the
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modelling tools to understand and tailor the physical and chemical interactions at the interfaces within metascintillators. Cranfield University’s Centre for Materials is internationally recognised
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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reinforcement learning, LLMs can iteratively improve by learning from feedback. If successful, this approach could present a ground-breaking solution for system software development. The candidate in this role
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Ultrafast lasers drive innovations from quantum technology to medical imaging, yet controlling femtosecond pulses remains a major challenge. Metamaterials are artificial structures with
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not fully capture the high-temperature, complex thermal-fluid interactions within the pebble-bed. This PhD project will focus on advancing porous media models for pebble-bed HTGRs by leveraging newly
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and ground), and boasts expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on ML-based co-optimization demonstrates some