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development and refinement accordingly. We are looking for a highly organised, driven, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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project, which encompasses 4-6 PhD studentships across 5 research groups, you will be an integral part of a dynamic doctoral cohort. This unique opportunity provides the successful candidate with the chance
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candidate will conduct fundamental research aimed at understanding cell shape dynamics and the cross -talk between cell shape and cell state during epithelial-to-mesenchymal transition (EMT). The aim
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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience
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students and post-doctoral researchers using high performance computing to advance understanding of high-speed aerodynamics. Over the past decade we have developed efficient open-source software that enables
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will dynamically adjust turbine parameters such as yaw, pitch, and torque to maximize Annual Energy Production (AEP) while minimizing component stress. Additionally, a hybrid predictive maintenance model
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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visual and sound sensory channels alone. However, it is currently not possible to undertake dynamic analysis of users¿ experiences in VR, and the aim of this project is to investigate how to assess
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, lack of transparency, safety assurance, and sustainability. You will work at the forefront of AI research, exploring formal and dynamic verification methods, explainable AI, and data space integration