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integration of energy systems data and models and apply data science methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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scenarios and strategies for its successful implementation. Using existing ICE-2 energy system models, you will address questions such as: How do installation and retrofitting times impact the restructuring
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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on a single cell level. This includes single-cell RNAseq datasets and analysis tools, large high-dimensional flow cytometry phenotyping panels and a collection of transgenic mouse models specifically
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experiments utilizing state-of-the-art approaches such as: Animal models of metabolic diseases and atherosclerosis Flow cytometric analysis of immune cell populations from murine tissues using full spectrum
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production, antibody binding assays, germ-free and gnotobiotic mouse models and human samples, bacterial transcriptomics, and single cell host transcriptomic analysis to obtain a detailed mechanistic
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integrate metabolic signals, establish cellular memory, and regulate plasticity. We use cutting-edge methods (multi-omics, single cell, live cell imaging, modelling, chromatin biochemistry as well as various
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of the epithelium, alarmin responses and Dendritic cell activation have all been implicated in the induction of type 2 immunity and potential differences between helminth induced and allergy associated type 2
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more