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Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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to another that can be viewed as heteroclinic connections between phase-locked states. The PhD project will consider the role that communication delays between nodes can have in shaping patterns of dynamic
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, usability, and insight into leakage dynamics across diverse constructions. Research Objectives The project is structured around three synergistic work packages: Descriptive Analytics: You will conduct a
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dynamic environments, including narrow spaces and interactions with unfamiliar objects. This project aligns with Rolls-Royce’s technical needs for developing soft robotic solutions to enable in-situ/on-wing
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integrates dynamic “smart” materials into 3D-printed structures, opens new frontiers in both bioelectronics and solar energy harvesting. Our goal is to create adaptive electrode architectures. These advanced
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skills, with a well-rounded academic background. Demonstrated ability to develop precision mechatronics/robotics systems and algorithm Ability to develop kinematic and/or dynamic analysis of mechanical
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analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices and mechatronics •Ability to develop kinematic and/or dynamic analysis
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-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability
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in both technical and potentially non-technical skills of medical staff, such as poor team dynamics, problems with communication and a lack of leadership. This automated obtained data can then be fed