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novel methods at the intersection of advanced control, optimization, manufacturing science, and machine learning, to create the next generation of sustainable automation solutions for modern manufacturing
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Professor Dr. Rama Gottfried at the Institute of Computer Music and Sound Technology (ICST) at the Zurich University of the Arts (ZHdK). Project background The project aims to develop theoretical and
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Research. The project is in close collaboration with the Computer Graphics Laboratory at ETH Zürich (Prof. Barbara Solenthaler PhD) who develops a fully virtual infant face and head model. The project will
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, or machine learning/data science applied to environmental problems. Project background Successful participants could use coupled global (CMIP) simulations, design and set up new model experiments using CESM2
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, or machine learning/data science applied to environmental problems. Project background Successful participants could use coupled global (CMIP) simulations, design and set up new model experiments using CESM2
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multiphysics phenomena and complex multiscale processes, as well as in developing and using innovative scientific computing techniques (including HPC, machine learning, multiscale algorithms). It also has
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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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multiscale processes, as well as in developing and using innovative scientific computing techniques (including HPC, machine learning, multiscale algorithms). It also has excellent experimental infrastructures
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simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal needs. Fluid injection or production induces changes in
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functionality and control Employing advanced control strategies and machine learning approaches, including imitation learning, for effective manipulation You will closely collaborate with other PhD students