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together: the backbone defines the interfaces, and your models make it realistic. Where and with whom You will join the Intelligent Electrical Power Grids (IEPG) section and work alongside the UTOPYS
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(particularly computer vision), (2) machine learning for data analysis, (3) sensor technologies (e.g., electromagnetic sensors), (4) design and integration of mechanical/electrical devices; and an interest in
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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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combining geophysical sensing, physical modelling, and artificial intelligence. You will: · design and conduct research using geophysical techniques such as Ground Penetrating Radar (GPR), Electrical
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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prototypes of a quantum computer and a quantum internet by integrating world-class research and groundbreaking innovation. Through excellence, relevance, and leadership, we cultivate a vibrant quantum
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the reference in the nuclear industry, but the current fleet of reactors will reach in a few years the end of their operating licenses. Generation IV reactors, among which the Molten Salt Reactor (MSR
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Job description Light water reactors (LWRs) are currently the reference in the nuclear industry, but the current fleet of reactors will reach in a few years the end of their operating licenses
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the films respond to external perturbations, such as molecular guests, light or charge. The focus will be on organic cages thin films as the key material class. The broader goal is to create robust, automated
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become oriented during film growth will be determined, and also how the films respond to external perturbations, such as molecular guests, light or charge. The focus will be on organic cages thin films as