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Field
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-scale neural network models. While the developed methods will be broadly applicable, particular emphasis will be put on the problem of inferring gas dynamics in urban environments. Gas dynamics shape air
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-Curie doctoral network funded by the European Commission under the Horizon Europe. GENIUS pioneers a comprehensive approach to address the biggest global challenge the energy sector is facing
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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 6 hours ago
the education of young researchers affiliated with the research projects of the transregio. To this end, the college provides training opportunities, guidance, and a pleasant networking environment in order to
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vulnerability to estimate future damage. These estimates linearly extrapolate historic data and assume that markets efficiently capitalize information about climate risks. This leads to gradual adjustments
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institutes as well as a secondment in a private-sector partner of the network. The research topics focus on the development of new physics inspired AI methods for inverse problems, uncertainty estimation and
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regularly in highly ranked international journals, and is often mentioned in both international and domestic media. The center has a large international network, and regularly organizes workshops and
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and pose estimation from ultrasound video, as well as designing a closed-loop robotic system for autonomous ultrasound scanning and navigation. In addition, the candidate will support the dataset
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challenges which experimentalists must consider – computer simulations of molten salts are therefore a very valuable guide to efficient experimentation. Molten salts have been well-studied using classical
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international conferences. This can provide opportunities for networking and learning from other researchers in your field. Extracurricular Seminars and Trainings The in-house umbrella organisation INGENIUM
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compositions. Initially, supervised learning models such as random forests, gradient boosting, and neural networks will be used to predict composition outcomes based on both literature scrapping and in-house