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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
algorithms to estimate human shape and motion in images, videos, RGB-D sequences, etc. Our approaches define the current state of the art. The Data Team is working closely with computer vision researchers
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in Germany. Founded in 1828, today it is a globally
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management and system design, energy process engineering and storage, grid planning and grid operation, grid stability and power converter technology, and thermal energy technology. Around 450 scientists
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Extensive hands-on experience in human iPSC or mammalian cell culture Preferred: experience in iPSC differentiation, organoid biology, or organ-on-a-chip technology Knowledge of imaging and/or molecular
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for real-time operation of AO systems Support experimental efforts by processing and analyzing image- and communications data streams Incorporate artificial intelligence framework into our AO systems and
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to process and understand large experimental datasets (e.g., image processing) #analyzing experimental results; developing conceptual models and parameterizations #scientific publication and presentation
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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materials and evaluate various electrocatalysts develop a laboratory prototype cell setup suitable for scale-up publish results in international journals develop market for electrolyzer technology
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the durability of materials and improve recycling processes. Be part of this change and explore cutting-edge methods in chemical, mechanical, and plasma processing of metal ores for a truly circular economy
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laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image processing) analyzing