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navigation services provider, has established the Centre for Doctoral Training in Air Traffic Management pioneering new research in machine learning and AI for air traffic control. During their first year
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systems, from sustainable energy grids to autonomous mobility. In this ERC-funded PhD project, you develop cutting-edge game-theoretic control and optimization methods. Job description Modern society
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significant reductions in manufacturing-related CO₂ emissions. The ambition is to develop innovative technological solutions that reduce energy losses and minimise environmental impact throughout the product
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selection criteria You must have a Master's degree in cybernetics, control systems, or equivalent, with a strong training in control of marine vehicles and/or robots. Additional training in machine learning
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significant reductions in manufacturing-related CO₂ emissions. The ambition is to develop innovative technological solutions that reduce energy losses and minimise environmental impact throughout the product
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investigate CO₂ desublimation under controlled cryogenic conditions. The project is primarily experimental, supported by modelling and data analysis. You will design, build and operate a cryogenic experimental
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with other scientists at TU/e and more recently within the newly formed Casimir Institute to develop the required solution for many of the relevant challenges in communication and sensing systems
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Are you fascinated by how machine learning can enhance control without compromising safety or stability? As a PhD candidate, you will develop scalable methods for expressive and flexible neural
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inexpensive microfluidic techniques. While the mechanism of these drops’ motion is well-known, controlling their trajectory is often challenging. There exist experimental proofs-of-concept that utilize imposed
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high-performance applications. The project brings together materials science, powder technology, additive manufacturing, and data science. Silicon carbide is widely used in demanding thermal, structural