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-agents for perception and communication. Candidates ideally have a background in computer science, electrical engineering, or related fields, and a strong interest in machine learning, optimization
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preservation from digital twins, so extra shelf life, to economical advantages. Integrate these digital twins into other platforms, such as mobile applications. Extend the digital twin work to optimize thermally
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, aligning AI systems with complex human values, and building self-improving agents capable of autonomous learning. Our work combines cutting-edge experimentation – spanning RL, meta-learning, and robust
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how perishable biological products, such as vaccines, react inside cold chain unit operations and to pinpoint why some products decay faster. For that purpose, we develop digital twins of the cargo
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possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions
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new generation of catalytic nanomaterials for water treatment, made of Earth-abundant elements and designed for their long-term performance. To fabricate and make these materials durable, the core
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applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be carried out in close collaboration with our interdisciplinary teams at both Empa and EPFL, as
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deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be
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-thinking approach to your work, while enjoying the challenge of learning and mastering new tasks? Are you creative, curious, and motivated to optimize, develop, and implement new ideas? If so, you are
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ETH Zurich is one of the world-leading universities for science and technology. At ETH Zurich, researchers experience a climate which inspires top performance. Situated in the heart of Europe, yet