525 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"L2CM" positions in Germany
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Work group: Institute of Coastal System Analysis and Modeling Area of research: Scientific / postdoctoral posts Starting date: 30.10.2025 Job description: Data scientist for geoscientific data
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Future. Discover. Together. The Computer Vision & Graphics group of the Vision & Imaging Technologies (VIT) department is looking for a student assistant in the area of deep learning for scene
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silicon wafers generates large data sets from extensive physical measurements. Efficient data preparation is therefore essential for short learning cycles. Your task is to enhance and implement automated
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digitalization team of the departments »High performance materials « and »Modular production machines «, we deal with the development of the control software of production machines and data-driven optimization
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5 Dec 2025 Job Information Organisation/Company Tübingen University Research Field Computer science Researcher Profile Recognised Researcher (R2) Country Germany Application Deadline 12 Dec 2025
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Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau | Landau in der Pfalz, Rheinland Pfalz | Germany | 4 days ago
science » Other Additional Information Website for additional job details https://jobs.rptu.de Work Location(s) Number of offers available1Company/InstituteRPTU University Kaiserslautern
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FRESCH and support our research priorities, we are looking for a Postdoc (gn) – Data Scientist (Reference: 31-FRESCH) Your tasks: Extract data from existing databases containing in-situ observations and
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focus on agent-based modeling and the quantitative analysis of spatial structures in experimental data. In doing so, you will develop your own research focus, support conceptual work, and contribute
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, the Helmholtz Association is Germany's largest scientific organisation. Where to apply E-mail karriere@fz-juelich.de Website https://www.fz-juelich.de/en/careers/jobs/2026D-007 Requirements Additional Information
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the characterization of these components on 300mm silicon wafers, large amounts of data are generated by extensive electrical measurements. An efficient preparation of data is therefore crucial for short learning cycles