129 machine-learning "https:" "https:" "https:" "https:" "https:" "VIETNAMESE GERMAN UNIVERSITY" positions at Leibniz in Germany
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willingness to learn German We offer Access to an international network of scientists, policymakers and research organizations An attractive job within the inspired and dynamic working environment
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January 2026 to (see button e-mail application below). https://jobs.zalf.de/jobposting/af3d771faf0a6dcc04a638f8f0d8f039bd501f6f0 If you have any questions, please do not hesitate to contact us: Dr. Ehsan
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on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/ With the application you agree
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comparable biological qualification An interest in the biology of invertebrate animals and a willingness to deal with living and dead molluscs Ability to dissect and determine molluscs, or willingness to learn
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
until 15 January 2026 to (see button e-mail application below). https://jobs.zalf.de/jobposting/70f91c6251650b58347f943683a60c00ccd3b5750 If you have any questions, please do not hesitate to contact us
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information at: http://www.ifw-dresden.de . The Institute for Metallic Materials (Prof. K. Nielsch) of the IFW Dresden offers a Post Doc Position (m/f/div) on the following topic: Project Coordination and Build
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For any questions on corrent topics, please contact: Prof. Dr. Antonella Di Pizio (a.dipizio.leibniz-lsb(at)tum.de ). More information on the working group can be found here: https://www.leibniz-lsb.de
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on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/ Please visit our website
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strong foundations in machine learning and artificial intelligence, as well as a solid mathematical background. The position requires a strong interest in exploring multiple research directions toward
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based on machine learning. Reference number 08/26 Your tasks 1. Assessment and analysis of GaN technology characterization data Identification of outliers during testing, with and without machine learning