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of such products. The work involves conducting a life cycle inventory, on-site observations in the wood and adhesive processing industries, and engaging with stakeholders for the sustainability and climate impact
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Galileo missions and the Hubble Space Telescope. This project uses computer simulations to study plume-plasma interactions and compares results with spacecraft data. The project leader is Associate
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high-quality research on interpretable and learning-based stochastic optimal control for over-actuated electric vehicles, with a focus on ensuring robustness and fail-safe operation. You will: - Develop
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, thermal dynamics, and charging strategies. Validate methods through simulation and collaboration with industrial partners (Volvo Group). Publish results in leading journals and present at international
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vehicle testing with human test subjects on test tracks and prototype vehicles Perform a benefit analysis of the proposed algorithms using simulation. You will collaborate with researchers from Chalmers
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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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properties of ultra-thin silica membranes (through e.g. transmission electron microscopy). There exist opportunities for being involved in the HCF fabrication process. The project is part of a consortium
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(DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global
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works in plants. Our group has developed several tools allowing genetics, microscopic, micromechanical and computational dissection of this process (https://www.upsc.se/researchers/6177-verger-stephane