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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. The Nonlinear Systems and Control group is seeking a talented and ambitious Postdoctoral Researcher
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
from all backgrounds to join our community. The Nonlinear Systems and Control group is seeking a talented and ambitious Postdoctoral Researcher to develop machine learning-enabled approaches
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to collaborate effectively with colleagues and project partners. Specifically, you have: Education: A PhD in a relevant field, with knowledge of structural mechanics, masonry mechanics, nonlinear finite element
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of the following areas: robotics, machine learning, robot perception, underwater systems, nonlinear control, system modelling, or autonomous manipulation Strong programming skills and a solid
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Control of Electrochemical Reactions This new project is a collaboration between our group and the Interface Science Department of the FHI, and combines the expertise in nonlinear infrared spectroscopy
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ultrafast nonlinear optical spectroscopy techniques—such as transient absorption and impulsive vibrational spectroscopy—the role aims to probe polariton-controlled electronic and nuclear dynamics occurring
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, “Time-Varying Operator-Theoretic Framework for Tipping Point Prediction” (PI: Prof. Sho Shirasaka) in the JST PRESTO research area “Exploration of New Science Using Mathematics to Predict and Control
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on advanced nonlinear optics and ultrafast laser techniques. The experimental work will be carried out on a table-top HHG beamline, producing XUV pulses with durations in the tens-of-femtoseconds range
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control the properties of the output laser beam and to focus it on the workpiece makes fibre lasers indispensable to modern manufacturing. As we enter the Digital Manufacturing/Industry 4.0 era however, new
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]. These systems are characterized by highly nonlinear, anisotropic, and time-dependent responses governed by evolving internal mechanisms and environmental conditions, making their predictive modeling particularly