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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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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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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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or more of the following areas: (1) Generative AI and machine learning, (2) affective computing, (3) human-computer interaction or collaborative AI, and (4) interaction design, experimental design or
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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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what you are going to do Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools
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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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postdoctoral researcher, you will lead the human-computer interaction side of the project. You will investigate how everyday athletes and coaches currently use tracking and feedback technologies, design and
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry