645 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs in Germany
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9 Feb 2026 Job Information Organisation/Company Technical University of Munich Department Computer Engineering Research Field Technology » Communication technology Researcher Profile First Stage
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Your Job: In this position, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following
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, biochemical interactions and biological functions of small natural product molecules in and from plants and fungi ( https://www.ipb-halle.de/en/ ). Contact details: We are looking forward to receiving your
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behavior on crystal defects. Perform active research on the materials synthesis, characterization, and device fabrication. Receive individual trainings to learn state-of-the-art methodology, comprising
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experience with NMR and wet-lab chemistry Willing to work within a multidisciplinary and collaborative research environment Curiosity and excitement to learn Good knowledge of spoken English Our Offer: We work
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-friendly frameworks for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics. The research combines continuum mechanics, machine learning
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this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
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found in our guidelines for review under the following link: https://uni-tuebingen.de/en/12271 The successful candidate will be working in a highly collegial and family friendly work environment. The
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Master Thesis in Physics or Materials Science: Remanent phase shifter based on memristive technology
website: https://www.fz-juelich.de/en/pgi/pgi-7 and the website for the mentioned project (in German): https://neurosys.info/projekte/ Your Profile: Completed qualification for enrollment in the project
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estimation, causal discovery, and concept-based explanation techniques Integration of causal and XAI methods into machine learning pipelines within the CRC 1294 “Data Assimilation” Implementation, evaluation