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Field
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harmonized multi-model datasets of high-resolution decadal and multi-decadal scenario simulations for the three European target seas, and (ii) demonstrators of climate services at European Sea basin, coastal
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compartments. The successful candidate will combine cutting-edge in vitro and in vivo infection models, and both microscopy and flow cytometry-based readouts of infection to develop their independent research
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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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-of-the-art computational resources, enabling advanced simulations and modeling. Moreover, we actively collaborate with leading experts in laser diagnostics, automatic control, heat transfer, and life cycle
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, Chemical Biology, Biophysics). The ideal candidate will have strong research experience, publications, and background knowledge in: i) All atom and coarse grain molecular dynamics simulations for RNA using
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time
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continuum modelling and finite-element simulations of multicomponent, multiphase electrochemical systems. • Ability to manage own academic research and associated activities • Previous experience
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About us The Green Laboratory investigates tissue morphogenesis and the action of morphogens. We use animal models to investigate the physical morphogenesis of tissues. It is part of the vibrant and
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modelling and finite-element simulations of multicomponent, multiphase electrochemical systems. Ability to manage own academic research and associated activities Previous experience of contributing
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine