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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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of NanoLund, Lund University's large interdisciplinary research Centre on nanoscience and nanotechnology. A significant proportion of the research conducted at the department is in the field
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
Posting Information Posting Information Department Psychology and Neuroscience - 319100 Posting Open Date 08/19/2025 Application Deadline 09/02/2025 Open Until Filled No Position Type Permanent
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experience should cover basic chemistry analytical skills to large scale pilot experience, hands-on, and data analysis. This includes experience on corrosion, kinetics, emission impurities, and solvent
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, including large-scale data analysis, alpha signal research, and strategy performance enhancement. While there is some overlap with the Quantitative Systematic Trader role, Quantitative Researchers typically
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) for different scientific applications, including simulations, large-scale data analyses and AI. This will involve designing test protocols, building test benches to track power and energy usage, and running
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Center. DTU Biosustain utilizes these advances for microbial cell factory design to
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution