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) Strong knowledge of classical and modern control theory Experience in designing control strategies for energy-efficient fluid power systems Experience with modelling and control of hydraulic displacement
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. Control and dynamic systems: A solid understanding of control theory, dynamic modelling and autonomous systems. Experience with trajectory tracking, path following, model-based control, state estimation
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electrical engineering, control engineering, applied mathematics, computer science, or a related field A strong background in probability and statistics, machine learning, or control theory Interest in cyber
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loading, wave–current environments (e.g., wave kinematics, high-order wave theories), and vortex-induced vibration would be highly regarded. Familiarity with contact modelling and structural degradation
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controlling electrochemical interfaces across scales. Computational PhD position: You will develop an AI-enhanced multiscale modelling framework combining density functional theory, ab initio molecular dynamics
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psychology, combined with phenomenological theory on aesthetics, music, and subjectivity. The successful candidate will be working closely with the PI and other collaborators, investigating how musical