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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 hours ago
leading AI researchers. We are seeking a Research Engineer – Software Development or DevOps (m/f/d), 80 – 100 % with a diverse skillset to support researchers and engineers in turning research into high
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hours per week), based in Berlin. Your Tasks Development of software for the analysis, management, and interpretation of omics data Selection and benchmarking of algorithms, libraries, and tools
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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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What you will do You will develop, investigate and optimize processes for the realization of fiber preforms using MCVD technology as well as gas-phase or solution-doping techniques for active fibers
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production and prepare the product for further processing or shipping. You will prepare the production and testing processes, e.g., by attaching connectors or cutting films to size, and organize
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Your Job: Help us further develop the dynamic Jupyter4NFDI web frontend and contribute your own ideas and suggestions for continuously improving the user experience Develop new components
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network of other geoscience institutions in Potsdam and Berlin. This largest regional concentration of geoscientific competence in Europe offers first-class cooperation and development opportunities. In
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 3 months ago
installed ‘Brain Algorithms and Circuits’ research group of Dr. Gregor Schuhknecht is searching for a Doctoral Student (m/f/d). About the lab Our research interest is to investigate how the synaptic circuitry
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offers first-class cooperation and development opportunities. In section 1.2 Global Geomonitoring and Gravity Field (Department „Geodesy“), we are looking for two positions: Reference Number 10837
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to develop automated algorithms for downscaling drivetrain components for specific test purposes. Furthermore, you will perform multiple case studies to analyze the performance of the developed scaling methods