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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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information-theoretic security even against quantum-capable adversaries, making it one of the most mature and commercially relevant applications of quantum communication. However, current QKD links are limited
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models that combine anatomical and hemodynamic information derived from routine clinical imaging. By providing quantitative insights into coronary anatomy, blood flow, pressure, and wall shear stress
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lifespan of geothermal systems depend on the subsurface distribution of heat, fluid flow pathways, and recharge mechanisms and fluid chemical composition. These factors control the precipitation, dissolution
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dataset for the neural networks. A PINN model is developed for the potential flow model to obtain up to second-order nonlinear solutions for water wave interactions with marine structures. The developed
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conferences, workshops, and collaborative visits. Each student will also be entitled to a relocation allowance of up to $1500. Project 1: Observation Focused Current models predict that water worlds should
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households or companies. But energy data is not like images or text: it consists of time series living on a physical network, governed by power-flow equations. Off-the-shelf generative models produce data
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pathways. However, the current common practice is first to build complicated, “black-box” models and try to understand what they learned afterwards. This has the disadvantage that a) interpretation is still
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with LP2M teams (immunology, iPSC models) as well as from the project's international clinical and scientific network (Prof. Claus Peter Schmitt, Heidelberg; UCA GenomiX and MICA platforms, Nice
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Power-to-X systems. You will drive the development of system-level digital-twin and optimization methodologies, integrating electrolyzer models with renewable generation, power conversion, energy and