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Field
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Spectroscopy (MBI) conducts basic research in the field of nonlinear optics and ultrafast dynamics arising from the interaction of light with matter and pursues applications that emerge from this research. It
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inspired by notions of energy, leading to highly efficient, local learning rules. What are you going to do? As a PhD candidate, you will develop mathematical theory for learning in nonlinear and dynamic
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quantify the impact of nonlinearity on flow and transportin confined porous media. We put particular emphasis on three sources of nonlinearity: non-Newtonian rheology, large driving rates leading to dynamic
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(ILM), interacting with PhD students, postdocs, and master's students on related topics. We seek a motivated candidate holding a master's in physics, with skills in ultrafast/nonlinear optics or soft
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controllers for complex systems that are safe and verifiable by design. Information Neural networks can provide the flexibility needed to control increasingly complex dynamical systems, but their opaque and
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multiple techniques such as onboard safety monitoring, operating environment adaptation and real-time robust learning of uncertainties and nonlinearities within the dynamical system. In this PhD, the aim is
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the nonlinear dynamics of these networks using theory and numerical simulations. - Design and perform table-top robotic experiments that implement your learning algorithms in unpredictable environments. Who
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accordance with NTNUs guidelines for recruitment positions and the general criteria for the position. Preferred selection criteria A solid theoretical background in nonlinear control and the control of marine
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selection criteria A solid theoretical background in nonlinear control and the control of marine vehicles or robotic systems. Additional training in machine learning methods is an advantage. Solid programming
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and Ultrafast Optics group led by Prof. Dr. Jens Biegert. The group works in a highly interdisciplinary field which fuses ultrafast laser physics, extreme nonlinear optics, atomic and molecular