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injury, and repair in experimental models of multiple sclerosis. Designing, implementing, troubleshooting, and optimizing experimental approaches. Developing and executing studies utilizing transgenic
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placed on novel genes, for which our laboratory has generated multiple genetically engineered mouse models. We seek outstanding postdoctoral candidates with strong career potential to advance our
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supervisor: The final report model to be prepared by the fellow is available at the following link: https://ucppt-my.sharepoint.com/:w:/g/personal/ccabral_ucp_pt/ESnbf2LTfxFGj8NsKVEAe3IBi00sddFg238l4P7ziYmXTw
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, Electrical and Electronics Engineering, Earth Sciences, Remote Sensing, and Artificial Intelligence are also well-suited. (More details on PhD requirements can be found at: https://nusgs.nus.edu.sg
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and decision support for railway operations and maintenance. The successful candidate will work on developing, testing, modelling, and validating methods for DAS-based monitoring of railway
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, network analysis, and mathematical modelling — with opportunities to pursue independent research. Curious to learn more? Read further to discover more about this opportunity. The team The successful
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of business models, the data economy, ecosystems, various business support platforms and platform technologies. Depending on the applicant’s profile, the open position may be located in any of these three focus
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The University of Texas Southwestern Medical Center (UT Southwestern Medical Center) | Dallas, Texas | United States | 2 months ago
translational cancer biology Applying genome-wide CRISPR screening, single-cell genomics, spatial transcriptomics, and clinically relevant mouse models to discover new therapeutic targets. As a physician
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supporting documentation, proven experience in all of the following areas: natural language processing and machine translation (sequence-to-sequence modelling, NMT, glosses); deep learning, Transformers, and
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knowledge of deep learning architectures and, in particular, Large Language Models (LLMs). Knowledge is valued both in advanced prompt engineering techniques (e.g. few-shot learning, chain-of-thought