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position: Postdoctoral Research Fellow for Large-Scale Longitudinal Data Analysis in Empirical Education Research (m/f/d, E13 TV-L1, 100%, for 3 years with potential of extension for 3 more years) We are
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the project under: https://bio-micro.eu/ Your main work place will be at the German Institute of Human Nutrition in Potsdam near Berlin (https://www.dife.de/en/ ) in the Department of Molecular
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to the CEFR: https://go.fzj.de/languagerequirements ) Our Offer: We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you
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Max Planck Institute for Political and Social Science, Göttingen | Gottingen, Niedersachsen | Germany | 4 days ago
its consequences for political outcomes at various levels. The project relies on a multi-method approach, including quantitative analysis of news reporting on political violence, electoral and other
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data-driven analysis algorithms for the assessment of thin-film solar cell fabrication processes within NOMAD Oasis installations. The team is responsible for the installation and development of (meta
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Max Planck Institute for Political and Social Science, Göttingen | Gottingen, Niedersachsen | Germany | 4 days ago
the organization of workshops, writing deliverables, data management, and dissemination of project findings in general audience venues; Be affiliated with and take an active part in the research environment
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Historical–Comparative Curriculum Analysis for the German Democratic Republic (GDR) and the Federal Republic of Germany (FRG) (1945–1990). Job description: Scientific research work for the project: “Working
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PhD Positions Application Deadline 6 Mar 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Part-time Hours Per Week 26,26 Offer Starting Date 1 Jul 2026 Is the job
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green lab in Germany. For more information please contact: Prof. Volker Haucke; e-mail: haucke@fmp-berlin.de . Homepage: www.leibniz - fmp.de/haucke How to apply: On the FMP homepage please go to “https
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis