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Agentic AI is an emerging technology that fundamentally changes product development and evolution. We seek to study the implications of Agentic AI with the intent of accelerating the adoption
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Effective use of AI and AI agents requires high quality data. This research is concerned with studying what data companies should collect, how they should process it, where to store it and how
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the Swedish Center for Sustainable Hydropower (SVC). SVC promotes collaborative research across universities and industry to support the future of hydropower. Simulations will be performed using resources from
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control and its integration with learning-based motion prediction under uncertainty. - Validate methods through simulation and collaboration with industrial partners (Volvo Cars and Volvo Group). - Publish
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work will build on and extend an advanced in-house time-domain simulation tool for wheel–rail interaction and noise. The project is carried out in close collaboration with DB InfraGO, the German railway
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of waveforms for satellite communication and radar systems communication/radar system performance analysis using theory and simulation field tests in relevant operating conditions retrieval of geophysical
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on the hypothesis that the future of building design lies at the intersection of physically sound building simulation models and machine learning (ML) techniques. Key considerations include effectively integrating ML
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-fabrication processes for superconducting devices Automatic bring-up and calibration of quantum processors Design and simulation of quantum processors Optimal-control techniques for high-fidelity qubit
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the field of humanoid robotics and their successful deployment in industry? Do you find the idea of working on a high fidelity multi-body dynamics simulation and controls toolbox fascinating? The research
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role in scientific advances, from quantum simulation to datacenter interconnects. Our group has pioneered ultralow-loss silicon nitride waveguides, enabling advanced nanophotonic components. This project