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superconducting circuits. This project focuses on modeling the quantum dynamics of these circuits at the Hamiltonian level and optimizing their control. You will develop theoretical models and optimization
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urban catchments. Develop road designs that optimize water accumulation or flow. Create a framework for the selection and design of climate-adapted roads. The research will primarily involve hydrological
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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dynamics simulation and controls toolbox fascinating? The research of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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learning, generative AI, and multi-objective optimization. Evaluate and select design options based on user-defined parameters such as environmental impact, aesthetic value, and cost. Additionally, you will
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artificial intelligence), exploring future skills, and optimizing equipment management. You will work in close collaboration with major industry partners to collect and analyze real-world empirical data using
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circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano-fabrication processes for superconducting devices Automatic bring-up and calibration
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achieving an optimal fuel-air mixture within the cylinder. This project will utilize engine experiments and advanced optical diagnostics to investigate how engine geometry and fuel injection systems influence