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headed by Prof. Iber, which leverages imaging data to develop data-driven, mechanistic models of biological processes. The team employs cutting-edge computational tools and imaging techniques
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of material and construction, and to reconstruct historic building processes. While our approach is fully in line with traditional surveying and documentation methods, we strive to draw additional high benefit
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and simulation of laser manufacturing processes (e.g., laser cladding, additive manufacturing) and experimental validation using advanced facilities (high-speed optical and infrared imaging, in-situ
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, Matlab, C++) for developing new simulation frameworks or image processing algorithms Experience in or willingness to learn independently operating additive manufacturing systems (DED and LPBF), including
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humans. By using bio-/neurofeedback approaches, pupillometry, advanced functional magnetic resonance imaging, and electrophysiological recording methods, we intend to understand and modulate these crucial
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humans. By using bio-/neurofeedback approaches, pupillometry, advanced functional magnetic resonance imaging, and electrophysiological recording methods, we intend to understand and modulate these crucial
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of knowledge between the fields of computer vision and forestry. Job description The successful candidate will develop a comprehensive modeling approach to quantify tree species health and forecast tree species