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Biology, Department of Life Sciences, to develop intelligent systems that integrate metabolic modeling, omics analysis, and automated literature mining. About us The Department of Life Sciences conducts
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Description Ice and mixed-phase clouds remain a significant challenge for both observational methods and atmospheric modeling. However, recent advances in both areas offer promising opportunities for progress
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Ice and mixed-phase clouds remain a significant challenge for both observational methods and atmospheric modeling. However, recent advances in both areas offer promising opportunities for progress
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely connected
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of electrodes and catalysts for low temperature fuel cells, electrochemical hydrogen generation, batteries, as well as heavy metal removal from aqueous solutions. By designing well controlled model systems in
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generation, batteries, as well as heavy metal removal from aqueous solutions. By designing well controlled model systems in combination with powerful analysis and characterization techniques, improved