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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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approaches to analyze and predict food-effector systems. Key Responsibilities • Develop graph-based (multi-)omics analysis algorithms • Benchmark graph-theoretic against graph-ML approaches • Analysis of food
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passivity-based control, machine learning, and human-centered control paradigms. Design and implement algorithms for shared control between human operators and autonomous systems to improve safety
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text analysis and network analysis to examine processes of recognition, inclusion and justice in educational contexts. Z03 establishes a methodological infrastructure that integrates algorithmic
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to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, thenewly established Chair of Algorithmic and Structural Graph Theory offers a position as
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, their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the Chair of Algorithms offers a position as Research Associate
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Conduct comparative benchmarking and performance analysis against state-of-the-art studies Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate
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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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for a researcher as of the Feb. 1st, 2026 (PhD position) as part of the reserach project BANNER. Your tasks: Develop AI algorithms for real-time fault detection, fault classification, and failure-mode