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Field
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The University of Marburg, founded in 1527, offers a variety of excellent programs of study for around 22,000 students and confronts the important topics of our time through excellent research
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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, computational data analysis and microbial evolution, with a solid understanding of quantitative statistics and programming (Python, R, MATLAB, etc.). Additional expertise in ancient DNA, (bio)archaeology
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the funding agency. The position is initially funded until 31.03.2027, but an extension is envisaged. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. It
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoc on
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Excellent command of advanced statistical methods, such as network analyses, using the R programming language Strong publication record relative to the career stage, demonstrating research excellence and
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with e.g. powder diffraction Experience with wet chemical synthesis, e.g. nanoparticles A distinct advantage would be: Experience with high-level programming languages, e.g. Python Knowledge in magnetism
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2025 - 23:00 (UTC) Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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programming would be considered an asset. Proven record in publication of results in high-impact journals. Programming experience in at least one the following: C, C++, Fortran. Proven background in software
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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication