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develops solutions for a range of vision tasks via machine learning and deep learning algorithms. The SSUDIO project aims to identify various objects of interest from shipboard 3D scans by training computer
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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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Fellow (EB1)1, available in https://dre.pt/application/conteudo/127238533 and in accordance with the consolidated version with the changes resulting from the update, approved on December 10, 2025 by
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period of 12 months, possibly renewable up to a maximum of 36 months, scheduled to start on March 2026. 2. WORK PLAN AND WORKPLACE: The project will investigate the developed algorithms and methods
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee Our department is looking for a Research
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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requirements: Experience using deep-learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating on scientific projects. Publications on deep-learning topics. 4. Work Plan
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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating
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on methods to improve understanding of how machine learning algorithms work. Workplan: Literature review Design of an approach for the selected problem Empirical evaluation of the proposed approach Writing