141 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Forschungszentrum Jülich
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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the INW-1 machine learning team on data handling, online analysis, design of experiments (DoE), and data categorization to enable efficient and automated evaluation of operando experiments Collaboration
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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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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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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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Supervisors: https://www.fz-juelich.de/en/judocs Targeted services for international employees, e.g. through our International Advisory Service The position is for a fixed term of 3 years, with possible long
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outstanding infrastructure ENVIRONMENT: A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen https://tza-aachen.de and the Forschungszentrum
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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/judocs
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to industry partners to learn and set up on-site research Preparing scientific publications and project reports Your Profile: Strong motivation for an interdisciplinary project that combines physics and biology
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with