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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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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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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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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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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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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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-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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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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. At the Rolls-Royce UTC, we have developed advanced robotic systems capable of navigating cramped and hazardous environments, performing inspection tasks, and carrying out active operations such as machining
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience