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to explain biological phenomena and disease mechanisms by leveraging biophysical theory and mechanistic, mathematical modeling. Our interests include the inflammatory responses to infection, the organization
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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in a quantum microscope. Your tasks Planning and execution of optically-detected magnetic resonance experiments with diamond Analysis and modelling of the experimental data Carrying out literature
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-scale modelling, machine learning) High resolution analysis, monitoring of chemistry, structure and transformations at the atomic scale of buried interfaces and defects by correlated experimental
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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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species. Analysis of phage activity—both free and embedded in biomaterials—using in vitro biofilm models. Training and mobility: Research secondments at SHIELD partner institutions: University Hospital
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 30 days ago
biodiversity. NaviSense performs research in the areas of (1) animal navigation mechanisms and their underlying senses, (2) quantum effects at ambient temperature in model systems and biology, (3) ecological and
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electrolysis and fuel cells (SOEC and SOFC). By combining numerical modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic
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modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic performance in fuel cell (biogas) and co-electrolysis