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construction or related fields Knowledge and experience in data analysis and database management, as well as emerging technologies applied to the construction sector, such as BIM, scanning, machine learning
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experience in Machine Learning with a PhD degree from a university in Computer Science, or related fields, with a proven track record in statistical machine learning, deep learning, and graphical modelling
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strategies to design pulse sequences for high-resolution solid-state NMR under magic-angle spinning and static DNP in close collaboration with two PhD students working on these topics. The efficiency
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to exploit the large number of modes supported by the random structure to enable large-scale nonlinear optical operators for photonic machine learning and quantum optics. The former relies on the second
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will be involved in developing a new service for circular information management for construction elements and reality capture in existing buildings using computer vision and machine learning. It
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, machine learning, modeling, and custom hardware, we test our solutions in various real-world projects with industry. Project background We foster a culture of continuous improvement, transparency, and no BS
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machine learning tools are a plus Knowledge and experience with phase-field modeling are a plus A keen interest in computational mechanics and in scientific methods and research in general Your workplace
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, machine learning, modeling, and custom hardware, we test our solutions in various real-world projects with industry. Project background We foster a culture of continuous improvement, transparency, and no BS
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from the machine learning domain to improve data analysis You will be responsible for project meetings, reporting, scientific publications, and conference/seminar presentations You will supervise master
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knowledge and technology from research to Swiss machine, electrical and metal industries. The research group Materials, Processes and Sustainability at inspire offers in collaboration with the Advanced