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Experience with Fortran, Python and Linux Shell Experience working with large datasets Preferred but not essential: Knowledge of wind farm parameterizations in mesoscale models Experience in the field of wave
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preferably has strong programming skills and experience with the modeling and simulations of fluid or solid mechanics or ice sheet flow and deformation (for example by use of finite element/volume methods
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production environments, enabling predictive maintenance and data-driven optimization through centralized data platform architectures. Your research will focus on addressing current bottlenecks in data and
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. Your primary tasks will be to: Setting-up gas fermentation conversion systems. Cultivating and enriching mixed microbial consortia on carbon dioxide. Investigating electron flow to final metabolic
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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models
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applications for one to two vacant PhD scholarships within the the research area of Security and Risks to Democracy. The expected start date is 1 October 2025. The Department is currently developing a research
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key