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Field
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National Laboratory to accelerate materials discovery by integrating advanced 3D X-ray diffraction experiments, mechanistic modeling, and artificial intelligence. A powerful set of high-resolution 3D X-ray
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the offer. The position’s field of research The position is associated with a new research initiative at UiT on intelligent monitoring and resilience of railway and transport infrastructure in Arctic
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that underly improvements in word learning and other aspects of language development in the first few years of life. This will primarily involve collecting, analyzing, and writing up experimental data collected
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;Knowledge in the collection, processing, and analysis of data obtained from physical activity and exercise monitoring technologies (e.g., wearables, sensors, or equivalent systems);Knowledge of exercise
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scientific, word processing, spreadsheet or statistical software applications or program platforms including R, SAS, Python, and MPlus. Acquires Specialized Training. Attends trainings and skill development
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? Not funded by a EU programme Reference Number AE2026-0205 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt
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technologies into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word
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, please refer to the link: https://research.nottingham.edu.cn/en/persons/alain-chong ; Prof. Ying Weng is Course Director for Computer Science with Artificial Intelligence, Professor in Computer Science
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Biologist in the Gillani Lab in Computational Pediatric Cancer Research (https://gillanilab.dana-farber.org/). The Postdoctoral Computational Biologist will work on the analysis of genomic, transcriptomic
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modules from thermal and RGB drone imagery, leveraging existing public datasets and data collected from real installations. Integration of the drone inspection tool with an existing continuous monitoring