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-doctoral researchers, visiting researchers, master's students, etc.) Research Context Recent advances in mobile robotics have been driven by remarkable progress in perception, deep learning, and control
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the analysis of nonlinear phenomena in dynamical networks. These phenomena include tipping points and adaptation across multiple timescales, with applications in restoration ecology. Ecosystems are an
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letter) in scientific modeling, simulation and/or control of [BG4.1]complex nonlinear dynamical physical systems. Proven experience (pointing specific publications in the motivation letter) in
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instabilities, we combine fluid mechanics, acoustics, and combustion with methods from control engineering, nonlinear dynamics, and data-driven modeling (machine learning). We collaborate closely with
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, particularly due to the lack of generation inertia worsening power system stability. Control of such a complex system relies on detailed understanding and real-time modelling of the nonlinear dynamics resulting
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more efficient approach will be targeted. This work will also include the development of the laser’s feedback control systems, as well as its adaptation to planned 229Thorium ion spectroscopy
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Environmental Engineering (CEE). For more information, please visit: https://earthobservatory.sg , https://ntu.edu.sg/ase , and https://ntu.edu.sg/cee . We are looking to fill a total of 5 Research
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encouraged to apply. Applicants who complement existing Duke MEMS strengths in aeroelasticity and unsteady aerodynamics, experimental and theoretical fluid mechanics, nonlinear dynamics and stability, and
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and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post-Doctoral associates
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candidate - we will mutually agree on the direction of the research, ensuring it aligns with your goals and aspirations. Sounds good? Join us! Note: For more details please see https://binyshlab.com