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for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as
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-Performance Computing for Exascale" contributes to the design and development of numerical methods and software components that will equip future European Exascale and post-Exascale machines. This program is
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the TRACCS research program (Transforming Climate Modeling for Climate Services, https://climeri-france.fr/pepr-traccs/ ), which brings together the French climate modeling community. Its activities cover
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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), and advanced high-pressure techniques. Experience with vacuum systems, lasers, spectroscopy, or numerical modeling (e.g., plasma or molecular simulations) will be considered an asset. The candidate will
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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macroscopic designs for soft-tissue healing. The project will be conducted using in vitro models of bacterial adhesion and fibroblast proliferation in collaboration with University of Gothenburg and in vitro
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will