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application! We are looking for a PhD student in automatic control. Your work assignments You will work on a project on data driven control. In recent years, data-driven control in high dimensions has
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of Electrical Engineering. Project description: Autonomous vehicles for mining and mobile robotics for industrial processes require complex motion planning as well as safe model-based predictive control and
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at the Department of Functional Materials and Catalysis at the Faculty of Chemistry develops advanced porous materials (MOF and COF) for sensing, energy conversion and catalysis. This PhD project aims to control
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at the Department of Functional Materials and Catalysis at the Faculty of Chemistry develops advanced porous materials (MOF and COF) for sensing, energy conversion and catalysis. This PhD project aims to control
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conversion and catalysis. This PhD project aims to control the growth, alignment, and assembly of framework materials using external fields (electric, magnetic, or flow) to create structured, anisotropic, and
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at the Department of Functional Materials and Catalysis at the Faculty of Chemistry develops advanced porous materials (MOF and COF) for sensing, energy conversion and catalysis. This PhD project aims to control
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everyday life. Department of Engineering Cybernetics (ITK) Engineering cybernetics is the study of automatic control and monitoring of dynamic systems. We develop the technologies of tomorrow through close
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ultimately allow us to design robust, manufacturable, and effective passive flow control concepts using smart materials and geometries for the next wave of hypersonic flight. You will develop an end-to-end
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the project: https://www.anthrofuture.com . The employment duration is 3 years (36 months). Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years
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the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create interpretable, data-driven observers that enable physically grounded perception and control for robust