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coupled hydrological and groundwater modelling, combined with machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics
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civil and military operations“ and „operational analysis and evaluation“. The combination of these research focus areas provides an ideal platform for interdisciplinary research in simulation and
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Pandemic Disease in Preindustrial Europe (1300–1800): Combining History, Machine Learning, and the Natural Sciences (EUROpest)”, funded by the European Research Council (ERC) as an ERC Synergy Grant
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following through the online application system - https://www.leibniz-inm.de/en/job-offers-2/ Motivation letter CV (max 2 pages) Publication list Academic transcripts Contact details of 2-3 references
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/) and part of the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https
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management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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). Knowledge of computer architectures. Knowledge of embedded systems. Knowledge of developing systems with systems-on-a-chip (SoC) and FPGAs. Knowledge of scheduling is desirable. Motivation to pursue a
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four different AC-voltages, independent of the distance covered https://arxiv.org/abs/2108.00879 . Theoretical consideration indicate good prospects for maintaining spin-coherence of the shuttled
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz