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seeking a highly motivated doctoral student to study physics- and thermodynamics-informed machine learning (ML) for the mechanics of material failure. The project focuses on learning the effective behavior
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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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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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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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at ETH Zurich. Our mission is to accelerate chemical discovery using digital tools. We predict chemical reactivity and molecular properties using the tools of machine learning, computational chemistry, and
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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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our state-of-the-art behavior analysis pipelines based on the latest developments in artificial intelligence and machine learning. You will train and guide collaborators during experimental design and
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behavioural studies in VR, analyse behavioural and physiological data recorded during VR. Interpret the results in terms of human attention, curiosity and learning. Publish the results of the research
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, DevOps, and machine learning come together. You will take the lead in designing and implementing a collection of advanced web applications aimed at optimising the asset and maintenance management processes