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Field
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to complex and overlapping pressures. Climate change, geopolitical tensions, energy risks, and shifting trade patterns make disruptions more frequent and difficult to manage. At the same time, companies must
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modelling and simulation of complex systems reinforcement learning or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging
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network of relevant stakeholders, inside and outside of academia Your team This position is part of the project “New perspectives on the water cycle” within the Earth and Environment Sector plan that aims
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development and is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users. Three strategic nanoscience themes underlie the CFN
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range of industries face the challenge of managing increasingly complex stochastic systems, where uncertainty is inherent and data is abundant. These systems arise in diverse domains—such as manufacturing
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primary mission involves developing control strategies that enable robots to perform complex manipulation through tactile feedback. You'll focus on three critical aspects of the problem: sliding motion
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Offer Description Project: EIC Pathfinder APACE nr 101161312 ‘Towards biomimetic sunlight pumped laser based on photosynthetic antenna complexes’ Description of tasks: synthesis of functional dyes
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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-scale, complex project environments. This project is part of an ambitious research program to integrate real-time sensing, AI-based control, and governance analytics into the future of infrastructure and
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted