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and project developers in reusing them in new projects. Taking the Chalmers campus as a starting point, we are developing scalable, AI-powered methods, such as computer vision for street-view imagery
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streams, contributing to elevated environmental mercury levels and increased human exposure. It is estimated that around 300 tonnes of mercury are released annually through these processes, making them one
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increased human exposure. It is estimated that around 300 tonnes of mercury are released annually through these processes, making them one of the top three sources of anthropogenic mercury emissions worldwide
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engineers, and researchers in materials science and nanotechnology. We are developing the superconducting quantum devices, control circuits, firmware, and methods required to make the quantum computer a
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of Geoscience and Remote Sensing , we develop advanced methods and instruments to observe and understand the Earth system. Combining satellite, airborne and ground-based measurements with modelling and machine
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences (AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians
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that combine first-principles multiphase flow descriptions with data-driven components Formulate and implement parameter estimation and system identification methods for multiphase flow models Integrate