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Challenge: Predict long-term cardiac growth and remodeling in cardiovascular disease. Change: Develop multi-scale mechanobiological models for virtual human twins. Impact: Advance patient-specific
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empirical taxonomy developed by the PhD candidate. Model training and fine-tuning. Fine-tune large language models on annotated educational datasets collected during the project, ensuring the agent's
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industry. Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track
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40 scientists, postdoctoral researchers, and PhD students working on the interpretation of satellite observations, atmospheric modelling, data science, and the development of future Earth observation
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, cash flows, and long-term business viability. Your Role We are seeking a highly motivated and creative postdoctoral candidate to develop data-driven financial forecasting, planning, and scenario-analysis
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on developing multi-scale mechanical models to predict how printed inks behave under mechanical and environmental stress. Your role: Build multi-scale models and extend the Eindhoven Glass Polymer Model for latex
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responsiveness? How can AI-driven EO systems adapt in real time to uncertain, fragmented, or high-risk environments, including those with limited ground-truth data? What role will predictive models and real-time
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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Materials Science section at TU Delft is actively engaged in developing fundamental understanding for next-generation circular steelmaking. Using advanced atomistic modelling techniques, you will unravel
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development of a Density Functional Theory (DFT)-accurate machine-learned interatomic potential (MLIP) for the multi-component steel system of interest. Ultimately, this simulation-driven framework will allow