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planetary atmospheres. The Section also initiates and manages a wide range of related modelling, software and hardware R&D activities. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s
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functionalities that can further improve operational performance, such as the integration of predictive models, orbital dynamics knowledge, or drag-aware optimisation strategies to enhance manoeuvre timing and
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systems to operate safely and efficiently. Possible research directions include advanced flight control, model predictive control, nonlinear control, fault-tolerant control, cooperative control and aerial
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learning, understand their mathematical foundations, and connect them to space-related technologies and missions. The focus is on building rigorous models that explain and predict the behaviour of modern
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theory, control, and optimization to study the interaction of these factors. Some questions of interest include (but are not limited to): Modeling and analyzing strategic equilibrium problems with
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for predictive policing and surveillance, as well as data mining and threat detection to name some of the most prominent uses. This position will enable you to develop top-notch research in the areas of AI and
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-enabled mission planning, immersive XR training, predictive maintenance, and digital continuity. The environment is highly collaborative, combining ESA experts, industry partners, and research institutions
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to predict traffic demand, user mobility, and network conditions, enabling autonomous decision-making that maximizes network performance and user experience. A unique aspect of this research is the integration
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in development to ensure the materials are safe, affordable, and user-friendly. The project will also explore behavioural drivers, incentives, and innovative business models to stimulate adoption
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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel