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numerical modeling and validation of brain-inspired algorithms Develop circuit-plausible training and inference algorithms, and analyze their behavior in LTspice and Cadence Spectre Perform algorithm–circuit
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mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en
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Technology, Dep. ETI / Embedded Systems, we are looking for a researcher as of the 01.04.2026. Your tasks: Development of architectures and algorithms for adaptation of time-triggered systems based
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 6 days ago
systems. Key Responsibilities Develop graph-based (multi-)omics analysis algorithms Benchmark graph-theoretic against graph-ML approaches Analysis of food-related (multi-)omics data Your Profile The ideal
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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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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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predict food-effector systems. Key Responsibilities • Develop graph-based (multi-)omics analysis algorithms • Benchmark graph-theoretic against graph-ML approaches • Analysis of food-related (multi-)omics