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hold, or are close to completing, a PhD in robotics, robot learning, or a closely related field. You possess strong expertise in deep learning and robot navigation, with hands-on experience in deploying
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, and contributing to grant applications. The post offers opportunities to work with international research groups and contribute to open-source bioinformatics tools. Experience with deep learning
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 8 hours ago
. Description: Exploration to deep space will require unprecedented levels of reliability and resilience to ensure mission success. Studies have shown that a high percentage of faults that occur onboard
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and develop skills in the growth of cultured tissue, an area of growing academic and industrial interest Opportunities to develop skills in biophysical models of tissues and deep learning techniques Key
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
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to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and predict key climate variables such as precipitation and temperature which are essential
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deep learning, language modeling, and omics integration. Prepare and contribute to abstracts, manuscripts, and grant applications, and present findings at departmental seminars, conferences, and symposia
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understand, process, translate and generate SL efficiently. We invite applications for a postdoctoral researcher with a strong background in deep learning, unsupervised models, NLP and/or sign language
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-doctoral fellowship starting January 1, 2026. The project “LSST – A New Window into the Be Phenomenon” will use the deep, long-term and high-cadence photometry from the Vera C. Rubin Observatory/LSST