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Field
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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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, 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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: 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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reliability of the identification process. Key Deliverables: Designing empirical eye tracking studies to explore user characteristics, such as deepfake classification expertise and cognitive approach
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31.03.2025, Wissenschaftliches Personal The Supply Chain Management Research Group at the Center for Digital Transformation of the TUM School of Management, Campus Heilbronn, Prof. Dr. David Wuttke
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The scholarship is a collaborative effort focusing on industrial design and optimisation of product assembly, quality inspection, and assembly process optimisation. It is expected to be a cross-disciplinary
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Stig Brøndbo 14th April 2025 Languages English English English Faculty of Science and Technology PhD fellow in “LLMs based Knowledge Graphs towards Digital Twin Development in Green Shipping" Apply
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nearing completion) in Electrical Engineering, electronics engineering, power electronics, or a related field. Basic knowledge of Basic knowledge of power converter topologies. Basic knowledge of digital
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, power electronics, or a related field. Basic knowledge of power converter topologies. Basic knowledge of digital control of power converters Experience or coursework in device simulation tools (e.g
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be used effectively as a performance digital twin to generate high-quality engine performance models and produce required training data for the proposed project. This could be a good starting point for