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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno
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, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno-economic study, design and analysis of integrated systems. Experience with energy system
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Diego, USA). By bridging experimental neurophysiology with advanced algorithmic design, we aim to significantly enhance the understanding of high-dimensional neural activity patterns. The successful
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National Lab, University of Tokyo etc.), the PhD candidate is expected to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient
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science can be eligible if they possess significant, demonstrable experience with optimization using physics-inspired algorithms or quantum computing frameworks. The applicant must have submitted his/her
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effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
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that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing
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to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process
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physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data
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for testing newly developed algorithms is anticipated in mainland Norway, Svalbard, and abroad. Funding is also available for conference attendances and research visits with external collaborators. The position