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Field
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assistant system using multimodal AI methods to process vision, language, and audio signals with an application to human- robot interactions to understand and respond to human actions. The successful
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leading academic environment in this field, and contribute with our expertise in areas ranging from nanoelectronics, phototonics, signal processing, radio technology and acoustics to satellite technology
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, digital and mixed-signal integrated circuits Layout design for CMOS and OLED production Close cooperation with interdisciplinary departments and research partners (e.g. OLED technology and production
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theory and AI, combining argumentation theory and affect theory to understand the intertwined processes of cognitive information processing and affective sensemaking crucial for digital literacy. It asks
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. We are encouraging applicants with backgrounds in digital media and communications, economics, history, anthropology, sociology and related social science disciplines, and relevant disciplines
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of the steel processing and to act as virtual tool for the selection of new steel compositions and of optimum processing conditions. Advances in digital twins also lead to fewer experiments and less usage of raw
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by steel industry is the development of digital twins able to contribute to an excellent control of the steel processing and to act as virtual tool for the selection of new steel compositions and of
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: Programming in Python and/or R Data science (e.g., tidyverse, pandas) Machine learning (e.g., scikit-learn) Deep learning (e.g., PyTorch, Keras3) (Optional) bio-signal processing and brain imaging (e.g., EEG
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this field, and contribute with our expertise in areas ranging from nanoelectronics, phototonics, signal processing, radio technology and acoustics to satellite technology and autonomous systems. Knowledge
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the intersection of digital applications that have real-time requirements and quantum resources that are time-constrained due to the decoherence and volatility. CLASSIQUE is organized into four research thrusts