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Postdoctoral Research Associate (f/m/d) for an Interdisciplinary Research Project on AI in Education
of communicative AI appropriation by students and teachers in secondary schools and how this is interwoven with the data infrastructures, design decisions, data models, and algorithms of AI platform providers and
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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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on the creation and application of predictive simulation models Collaboration on the development of data processing and fusion algorithms Collaboration on the virtual modeling of marine structures Conducting and
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- conducting processors with respect to practical short-depth (NISQ) quantum algorithms Cooperate and actively work with experimental partners developing quantum processors using these technological platforms
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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. Utilize AI and statistical techniques to extract insights from large time series datasets. Collaborate within an interdisciplinary team to develop innovative algorithms for forecasting, ranging from short
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imaging with clinical text and decision support. Evaluate algorithms regarding robustness, explainability, and clinical impact in musculoskeletal medicine. Collaborate in an interdisciplinary team
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24.09.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, invites applications for a fully funded PhD position at the Technical University of Munich
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the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure
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Implement and document numerical algorithms for calibration, synchronisation, and data transformation in a modular, traceable workflow Validate Level-1B outputs, including spectral and statistical quality