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of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after
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processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative
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AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic
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description of cell wall strains and stresses and turgor pressures with sets of ordinary differential equations describing the biochemical networks regulating cellular decision making. Models will be initiated
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erythrocytes, alongside biomarkers of inflammation and oxidative stress. Using combined laboratory and clinical data, empirically derived algorithms for subphenotype identification will be developed through
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generation, steel production and cement manufacturing. One promising route is cryogenic carbon capture, in which CO₂ is cooled to very low temperatures and turns directly from gas into solid. This gas-to-solid
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) develops and applies innovative molecular imaging technologies that reveal biological processes across multiple spatial scales—from whole organs to individual cells and subcellular structures. Within
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This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing