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scalable methods for understanding the inner workings of large language models and developing functionally-grounded steering and control techniques. The successful candidate will contribute to frontier
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probabilistic modelling techniques for assessing and improving the performance of existing structures. The position is to be filled by February 1, 2026, or as soon as possible thereafter. The position is a five
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well as experience in automated fabrication and mechanical characterization. A solid background in modelling and system identification is essential, with particular emphasis on data-driven and machine-learning–based
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. Despite their potential, challenges remain in accurate modeling, sensing, and control due to their highly deformable and nonlinear nature. This PhD project aims to advance the navigation and control of soft
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complex anatomical structures such as blood vessels, the bronchial tree, and endoscopic pathways. Despite their potential, challenges remain in accurate modeling, sensing, and control due to their highly
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advanced mesoscale fluid simulations such as CFD, Lattice Boltzmann Method (LBM), Pore Network Modelling (PNM), and Molecular Dynamics (MD) with microfluidic experiments. The research targets gas bubble and
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team of appr. 60 researchers specialized in robot solutions involving modelling, estimation, and control of advanced robot technologies. The group is involved in a variety of national and European
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, and Maintenance Software Reliability Engineering Systems Engineering Model-Driven Engineering Modeling, Simulation and Data Analytics Human-Computer Interaction and Design Interactive Systems
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. We are a team of currently about 20 researchers, engineers and PhD students, specialized in robot solutions involving modelling, simulation, and control of advanced robot technologies (systems and