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support the development of a European energy system model by benchmarking future technologies and optimizing their representation within the FINE optimization modelling framework ( https://github.com/FZJ
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a Research Associate / PhD: Physics-informed deep learning for PDE-constrained optimization
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Your Job: Against this background, this PhD thesis aims to investigate how water availability affects the energy transition. The goal is to achieve a sustainable energy and water supply and to
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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future climate scenarios. Your research will contribute to understanding the effects of climate change on renewable power generation and its impacts on energy system design on a global scale. Key
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activity and stability as benchmarks for the evaluation of material libraries. The available PhD position mostly focuses on the following topics: Optimization of a high throughput electrochemical
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Application deadline Applications must be received by 15 August. Tuition fees per semester in EUR Varied Combined Master's degree / PhD programme No Joint degree / double degree programme Yes Description
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Your Job: Maintain, and update quantitative methods for assessing economic impacts of the energy transition at the national and regional levels Develop dynamic and multisectoral economic models
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Your Job: Among other applications, optimal control theory has proven its utility for the optimal calibration of quantum gates early on and has since been used routinely in experiments