137 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" positions at Leibniz
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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further both professionally and personally in an interdisciplinary setting. Position DWI is looking to fill the position as soon as possible: Research Scientist Machine Learning Engineer - AI-Powered Image
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. The positions focus on applied machine learning methods for real-world systems. Possible research directions include: Transfer learning and domain adaptation across heterogeneous production environments (e.g
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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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, starting 01.06.2026, ending 31.05.2030): Postdoc position (f/m/d) in the department “Competencies, Personality, Learning Environments” (Focus: socio-emotional and cognitive competencies) The Leibniz
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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your online-application as one single pdf-file (http://www.ipk-gatersleben.de/en/job-offers/) by 25.03.2026. If you have questions or require more information, please contact Kerstin Schweigert (jobs
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regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing date for applications is April 11, 2026. Please apply
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in