59 phd-studenship-in-computer-vision-and-machine-learning positions at Chalmers University of Technology
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the lab, you will be exposed to a broad range of computational methodologies, ranging from material characterization, via machine-learning and high-throughput methods, to ab initio calculation
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student, you will be supported by a multidisciplinary team with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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We invite applications for several PhD positions in experimental quantum computing with superconducting circuits. You will work in the stimulating research environment of the Wallenberg Centre
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Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
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. This unique position combines advanced finite element modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an
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Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and machine learning applications Experience with machine learning methods
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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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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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are looking for: To qualify as a PhD student, you must have a Master's degree (masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits in Machine Learning, AI, Data Science, Computer