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-time, on-site postdoc position based at TU Delft in Delft. The initial appointment is for one year, with the possibility of extension, subject to progress and project conditions. In this role, you will
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agentic AI systems and real-time inference pipelines. Awareness of Challenge-Based Learning or comparable active learning frameworks. Additional Information Benefits A meaningful job in a dynamic and
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further collaborations in the institute and the wider research community. Where you will work The Faculty of Science is a world-class faculty where staff and students work together in a dynamic
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learning and expand its safe use in space. This includes, but is not limited to, approaches based on statistical mechanics and thermodynamics of learning, dynamical systems and continuous-time views
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one or more of: physics-informed learning, world models, simulation / physics engines, dynamical systems, robot learning, or scientific machine learning; excellent programming skills (e.g. Python
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. Both signals and responses occur over time, in a dynamically changing landscape. The goal of this position is to investigate information transfer in dynamical systems, ranging from molecular
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researcher at TU Delft, you will develop and lead analytical and numerical research on the quantum dynamics of mechanical systems and their interactions with complex environments. Building on these models, you
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and deepen developed innovations. In this postdoc position you will be employed at the Multi Actor Systems Department and co-supervised by the Rotterdam School of Law. You will work together with a
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testing of AI-driven Earth observation systems, with a focus on the autonomous, decision-making capabilities that enable satellites to adapt to dynamic environmental changes and urgent events; collaborate
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complex dynamic system. Minor disruptions can lead to major delays with traffic jams spreading like oil spills over entire networks. We believe traffic management based on reliable predictions is therefore