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qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and
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therapeutic strategies, ranging from antibacterial to anti-cancer drugs. To this end, we develop new ways to combine state-of-the-art technologies in metabolomics with mathematical modeling. The candidate will
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combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
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of cardiovascular anatomy and hemodynamics. The research will integrate modern machine learning with MR signal modeling, computational imaging, and fluidmechanis, with the ultimate goal of enabling faster, more
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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of applying molecular models at process scales, the project combines efficient mathematical concepts like automatic differentiation with backpropagation – the same concept that powers machine learning and
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systems, and space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where
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learning environment. Your main tasks will be: Establishing models of B and T cell priming in human lymphoid organoids. Performing characterization of organoids and primary samples with flow cytometry and
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-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative disciplines
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learning environment. Your main tasks will be: Establishing models of B and T cell priming in human lymphoid organoids. Performing characterization of organoids and primary samples with flow cytometry and