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position is part of a research project that investigates the contribution of marine microalgae (phytoplankton) to natural climate protection. The successful candidate will research phytoplankton abundance
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Your Job: Hydrogen is a key element of the energy system of the future. However, in many processes it is only produced in limited purity and/or is only available at low pressures. Your task is to
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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of the components of the climate system. As a suitable candidate you, have expertise in analyzing complex systems (e.g., using dynamical systems theory, statistical physics) and/or process-level expertise in a
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) to conceptualize and quantify the controls of anvil extent and cloud feedback of tropical deep convection across scales. As a successful candidate, you will combine your expertise in deep convective processes with
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, the European “Green Deal” and the phase-out of lignite. Funded by the German Federal Ministry of Education and Research, the project focuses on two central aspects: accelerating technology development and
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Navigation Satellite Systems) are crucial for positioning and timing but are vulnerable to natural and man-made interference—as recently observed in the Baltic Sea region. R-Mode (Ranging Mode), developed by
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Your Job: Combine multimodal brain imaging with advanced image-processing, data science, and AI techniques to perform image alignment, segmentation, and classification to construct and validate
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, including next generation sequencing data processing is an added advantage excellent command of written and spoken English pro-active learning and desire for career development excellent communication and
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research outcomes to project stakeholders and the research community at meetings, conferences and by publishing in high-impact journals This position is within the Quantum Information Processing research