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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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or natural sciences Sound knowledge in machine learning algorithms, statistical methodologies, and biological network analysis Experience with the analysis and integration of transcriptomic and multiomics data
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Iterative Algorithms: Optimization and Control.” About the Project The focus of the project is the analysis of iterative algorithms arising from time discretizations of nonlinear evolutions of various kinds
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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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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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algorithms for computing equilibria. Positions Available We invite applications for Doctoral Researchers (Ph.D Candidates) and Postdoctoral Researchers These full-time positions (100%) are initially offered
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systems. Design and implement algorithms that enable shared control between human operators and autonomous systems to improve teleoperation performance. Maintain active communication and collaboration with
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and