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, and/or computational modeling. This position integrates rigorous experimental characterization with multiscale simulation to understand failure mechanisms and improve safety at the cell, module, and
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predictive models for failure control. Validation & Experimental Collaboration: Compare simulations with experiments, collaborate on proof-of-concept testing, and refine models based on results. Where to apply
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of the contact line, which is still only partially understood and predicted. The present thesis proposes to develop an original experimental approach based on the simultaneous coupling of several optical
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genetics to predict breast cancer risk and tumour aggressiveness in BRCA variant carriers Digital biomarkers for enhanced AI-guided therapy in heart failure (D-BEAT) Experimental models for optimizing
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workflow that maps first-principles electronic-structure data onto predictive atomistic spin-Hamiltonians and device-scale dynamical models. The candidate will run high-throughput, relativistic DFT
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approaches capable of guiding experiments, interpreting results in real time, generating predictive models of materials synthesis processes, and refining experimental strategies under a Human-In-The-Loop
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opportunity to work in a top-tier interdisciplinary setting. This is what you will do You will develop predictive computational models to capture the formation and heterogeneous structure of microthrombi, with
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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methodologies, advanced controller synthesis, performance and stability assessment. Trade-off, prototyping and selection of advanced DFAOCS control methodologies: minimum set to be explored: model predictive
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intelligent decision architectures, predictive analytics, and adaptive computational models that can operate in dynamic, uncertain, and high-stakes project environments. The appointee will conduct original