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Field
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solution for the future of maritime decarbonisation. Your work tasks The research assistant will be involved in high-fidelity numerical modelling and a comprehensive analysis campaign of flexible power
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at the commuting-zone level to analyse impacts on employment dynamics, wages, worker mobility, and regional divergence, as well as evaluating whether the diffusion of large language models (LLMs) is itself reshaping
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, including high-throughput bioreactor cultivations, multi-meta-omics (metagenomics and metaproteomics), and mathematical modelling. You will work in a highly interdisciplinary environment at the interface
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research and artificial intelligence can be combined to improve planning and operational decision making under uncertainty. The project addresses challenges that arise when traditional optimization models
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for teaching and research for the tenure track period CV including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching
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) (departments of Mathematics and Computer Science as well as Biology, Chemistry and Pharmacy) and the Max Planck Institute for Molecular Genetics (MPIMG). Courses, seminars and joint research work foster the
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. The following typical research topics serve as interdisciplinary links between the various fields of systemic neurosciences: single cells to complex systems system analysis to mathematical modelling perception
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applications in different project contexts. This may include data analysis, modelling, literature reviews, and interaction with relevant stakeholders. The results are expected to contribute increased knowledge
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and passive RF localisation using software-defined radio. A central theme of the project is co-design across sensing, AI reconstruction, and embedded deployment. You will explore how multimodal models
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element simulations, blast loading models, propagation of pressure waves in the ground and soil–structure interaction analyses to establish methods for assessing the protective capacity of existing