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systems coupling sensing, internal regulation, and body dynamics. Inspired by nonlinear physics, we will investigate normal forms (i.e., universal weakly nonlinear descriptions) and determine when such
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fields like communication, energy, health, and mobility. The focus in the RF Power Lab is on applications with output powers in the range of 5...200 W in the microwave range up to 40 GHz. We work on novel
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National Institutes of Natural Sciences, National Institute for Physiological Sciences | Japan | 21 days ago
of brain and neural functions. We achieve this by developing novel super-resolution microscopy and related systems, leveraging advanced optical and laser technologies. [Work content and job description
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pipelines, and rigorously quantify reductions in energy per solve compared with optimized CPU/GPU and FPGA baselines. The project targets three real THz-NDE use cases: (i) sparse deconvolution of THz impulse
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, the parameter adjustments are usually performed in a brute-force manner, without considerations of nonlinear coupling between multiple parameters. As a result, the models (that reproduce the data that they were
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accepted all year round Details Model predictive control (MPC) is a popular advanced control technique that solves a constrained optimal control problem, on-line, at each sampling instant. The first control
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optimization of nonlinear problems will be essential. The researcher must also be familiar with image manipulation and software development in Matlab or Python. The ability to collaborate both in academia and
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parameters. In parallel, the candidate will gain in-depth knowledge of time-modulated photonic media, nonlinear optics, adjoint-based optimization strategies for high-dimensional inverse design, and realistic
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operation. To design optical metasurfaces and material platforms exhibiting time-varying responses. Using adjoint-based optimization and spatial structuring, to realize complex time-modulated medium dynamics
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optimization, including integer, nonlinear, and combinatorial optimization; global and non-convex optimization; machine learning for optimization; explainable artificial intelligence; heuristic and metaheuristic