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for advanced courses, international research visits, and networking across Sweden’s top universities. Information about the research group The Computer Vision Group at the division of Signal processing and
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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gathering knowledge about the diverse physical and geometric properties of objects and dynamic changes in the environment. This involves leveraging rich sensory data—such as vision and touch—encoding
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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. The position is placed in the Division for Computer Networks and Systems and is formally employed by Chalmers University of Technology. Our research spans from theoretical computer science to applied systems
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failures. We offer access to unique experimental data and computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel
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(advantageous but not required). Familiarity with using digital technologies in construction, like BIM (Building Information Modelling). Main responsibilities Participating in the Graduate School of Civil and
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of the numerical methods behind CFD and turbulence models. Experience in analyzing CFD data and interpreting simulation results. Excellent command of written and spoken English. Experience writing scientific reports