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Field
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of generative AI and foundation model approaches for smart grids and energy systems Generation of synthetic yet realistic energy datasets based on real operational data from the FZJ campus and Living Lab Energy
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produce data that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models
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transport, with the ambition of producing high-impact research and contributing to Iceland’s climate neutrality goals by 2040. The PhD project investigates the ancillary services and grid upgrades required
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to watch video, or click here to open video) About the position We are looking for a PhD research fellow within “Distributed Optimization and Control of Reactive Power considering grid stability in
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From electric vehicles to grid-scale energy storage, the future of clean energy relies on breakthroughs in battery technology. This PhD will develop cutting-edge terahertz spectroscopy methods
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systems, from sustainable energy grids to autonomous mobility. In this ERC-funded PhD project, you develop cutting-edge game-theoretic control and optimization methods. Job description Modern society
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that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models for energy-system data
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embedded into cyber‑physical systems (CPS) such as autonomous vehicles, smart grids, industrial control systems, robotics, healthcare devices, and intelligent transport infrastructure. While significant
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that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models for energy-system data
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monograph. The two positions. We are recruiting two PhD candidates within GRID: Position 1 — comparative cross-national: developing and analysing the cross-national dataset to test the project’s theory across