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The Data-Driven Mechanics Laboratory is seeking a highly motivated doctoral student to study physics- and thermodynamics-informed machine learning (ML) for the mechanics of material failure
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- Transport Mechanics group and within the scope of a research project funded by SwissNuclear we are looking for a Postdoctoral Fellow for machine learning enhanced multiscale reactive fluid dynamics Your tasks
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testing of the interactive interfaces. The visual interface will be built with Apple Vision Pro. Your profile Solid programming experience in C#/Unity, Python Knowledge of human-computer interaction
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record in robot navigation control or deep learning optimization for sensor fusion. Highly motivated, self-driven, and shows excellent performance. You have first-rate oral and written English skills and
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systems, and control with a PhD degree from a university in Computer Science, Robotics, Mechanical Engineering, or related fields, with a proven track record in robot navigation control or deep learning
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revolutionizing image reconstruction and analysis with state-of-the-art machine learning techniques. Ultimately, we aim to provide personalized diagnosis and therapy for optimal patient outcomes. Job Summary We