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Field
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candidate would have experience with computational modelling and control of dynamical systems. Other useful skills include scientific programming (e.g., Python or Matlab), control system design, and
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Mechanical, Materials, or Biomedical Engineering, or a related field. Interest in biomaterials, mechanobiology, or modelling. Familiarity with computational tools (Matlab, Python, or finite element analysis
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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this project, the student will develop skills in: the structure of weather and climate models, interrogating weather and climate models with observations from the British Antarctic Survey, computational
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of OI fractures and its management. The successful candidate will have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing
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for fine-tuning and deployment of large-scale models. What’s more, multimodal models are particularly vulnerable to data uncertainty, modality dropout, and noise propagation, which can degrade robustness and
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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, or modelling. Familiarity with computational tools (Matlab, Python, or finite element analysis). Analytical thinking and enthusiasm for interdisciplinary research. Ability to work independently and as part of a
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allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. Overview The state-of-the-art in computer-aided drug design is physics-based modelling, in which candidate drugs and
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling