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Location: Luxembourg, Luxembourg 1511, Luxembourg [map ] Subject Area: Quantum LDPC codes with efficient decoding algorithms Appl Deadline: none (posted 2025/08/05) Position Description: Apply Position
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actively contribute to the WeForming and EnerTEF projects. WeForming and EnerTEF propose developing automatized and intelligent solution for operating active distributed grids with multiple active asset6s
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations
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the opportunity to investigate a broad range of research areas with particular focus on understanding the foreseeable adoption of various energy technologies related to e-mobility (e.g., distributed
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security—including food distribution, nutrition, and the socio-economic drivers of inequality. Using a global lens while remaining rooted in national, regional, or local contexts, preferably in the Global
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surface properties. Many of these properties are believed to represent adaptations to specific environmental conditions, resulting in distinct distributions of certain combinations of leaf properties
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technologies used in and connected to grids (e.g., distributed generation, storage, electric vehicles, heat pumps, smart energy management systems, etc.) and how to design grid tariffs that align grid and market
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verticals, Unmanned Aerial Vehicles, Integrated Satellite-Space-Terrestrial Networks, Quantum Communications and Key Distribution, Spectrum Management and Coexistence, Tactile Internet, Earth Observation, and