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expertise in nonlinear optics in optical fibers and planar waveguides. The activities within the project will benefit from synergies with other projects in the group as well as with other activities
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aims to develop hybrid quantum–classical approaches for modeling multiphase flows governed by complex, nonlinear dynamics across multiple scales. The postdoctoral researcher will investigate how
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
languages (e.g., Python, Julia, Matlab) Strong interest in process modeling and simulation, including novel methods and approaches such as neural networks and nonlinear optimization Ability to analyze complex
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diffraction tomography, with a focus on inverse multiple-scattering algorithms. Implement and evaluate both linear approximation models and nonlinear high-order scattering approaches for accurate imaging
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, 100% funded PhD student position to fill starting around June 2026. Research is to be in the field of computational methods in nonlinear and large scale optimization / inverse problems or in novel
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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 from
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improvements. Examples include optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques
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mathematics and simulations, applied mathematics modelling, nonlinear science, wave propagations in lattices, fluid mechanics and financial mathematics. About You The successful candidate will be expected
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systems. However, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification. Typical identification algorithms
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, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification -- one notable example is given by Gaussian process