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considered. Applicants should provide a curriculum vitae and a copy of official transcripts of diplomas and grades from all academic institutions of higher education listed in the CV. In addition
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equal opportunities Support in balancing work and family life Extensive advanced training opportunities Occupational health management offers Flexible working time models Opportunity to work remotely The
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combines microbial genomics, transcriptomics, and in vitro infection models to explore the adaptive trade-offs between drug resistance and virulence phenotypes. The position is funded for 3 years and
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quantification, model-order reduction, or multi-fidelity methods. The primary fields of application are life science, medicine and health, earth observation and robotics. Consequently, a MUDS student will learn
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resource efficiency. A physics-based model for monitoring the condition of helicopter components is being developed as part of this project. With the help of flight test data, this model is to be calibrated
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interfaces hosting two-dimensional electron and hole gases. Closely collaborating with experimentalists, we will develop effective models to predict the spin/orbital textures, topological textures, and
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Scrum) and modeling of system structures and behavior. Experience with common software development tools, for example Git, IDEs, CI/CD and issue tracking. We offer: A family-friendly and collegial working
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for the scaffold protein SANS which has been related to the microtubule-based intracellular transport in the cytoplasm of the cell and ciliogenesis in primary ciliary cell models and retinal photoreceptor cells
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to): Transparency and contestability in AI Accountability in algorithmic infrastructures Technical mechanisms for evaluating and auditing AI systems Governance of open-source and general-purpose AI models Data rights
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-situ measurement network and perform terrestrial laser scanning, analyzing microclimate data and their relation to forest structure, and using optical satellite time series and radiative transfer models