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at the Department of Chemistry at Freie Universität Berlin starting October 1, 2025, in one of the following projects: Job description: Contribute to research in one of the following projects. Please, indicate your
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the project “Modeling Great Ape Signaling Behavior” under the auspices of the Collaborative Research Center “Common Ground” (CRC1718), which is funded by the German Research Foundation (DFG), at the University
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% of full time E13. The position is associated with the project “Modeling Great Ape Signaling Behavior” under the auspices of the Collaborative Research Center “Common Ground” (CRC1718), which is funded by
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diagnose and treat human infections. HIRI is a site of the Braunschweig Helmholtz Centre for Infection Research (HZI) in cooperation with the Julius-Maximilians-Universität Würzburg (JMU) and is located
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of suitable process parameters for PBF techniques, and the comprehensive analysis and testing of the fabricated materials. Key responsibilities include: scientific work on the project topics, including support
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diagnose and treat human infections. HIRI is a site of the Braunschweig Helmholtz Centre for Infection Research (HZI) in cooperation with the Julius-Maximilians-Universität Würzburg (JMU) and is located
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Engineering, Information Systems, Mathematics, or a related field. Strong knowledge of software engineering (e.g., software architecture, development processes, quality assurance). Very good programming skills
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(deboah.wiltshire@gesis.org ). If you have questions about the application process, please contact Ms. Franca Tosetti via E-Mail (franca.tosetti@gesis.org ). Interested? Please apply via our Online-application
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, geoinformatics, Data Science (Natural Language Processing), computational linguistics, taxonomy (especially entomology), or ecology with strong data skills Experience with text mining of scientific and historical
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training