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the group, translating cutting-edge deep learning algorithms into robust, maintainable analysis tools and pipelines Implement and optimize large-scale deep learning workflows on GPU-enabled High-Performance
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leverages AI and cutting-edge infrastructure to optimize EV charging and energy systems. By integrating distributed energy resources, demand response, and storage, it aims to enhance grid flexibility and
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SD-26109- POSTDOCTORAL RESEARCHER IN AI-BASED ENERGY MANAGEMENT OF RESILIENT MICROGRIDS WITH SECO...
grid disturbances, outages and high uncertainty. Optimizing battery system operation, including state-of-charge management, reliability, lifetime-aware operation and backup power availability. Building
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) for SLAM and environmental awareness in GNSS-denied conditions Adapt hierarchical mission planners to decompose high-level defence missions into executable, EW-resilient tasks Optimize algorithms
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involve various aspects of the modeling and the optimal control of active systems. The candidate is also expected to take part in the scientific activities organized within Physics of Active Matter group
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Luxembourg Institute of Science and Technology (LIST) | Luxembourg, | Luxembourg | about 2 months ago
digestate, advancing the technology from bench to pilot scale (TRL 4–5). The work encompasses three main areas: (1) process optimisation, using AI-assisted experimental design to identify optimal operating
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modeling, reinforcement learning, optimization for learning, trustworthy and efficient machine learning, or foundation models including large language and multimodal models. We particularly value depth
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learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab
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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab, the HybridNetLab, the QCILab
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-driven modeling or systems optimization. Experience 0–3 years of postdoctoral experience (or equivalent research experience) in computational, statistical, or data-driven modelling Proven experience in