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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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new knowledge with a clear academic and social impact, in fields such as AI-enhanced translation workflows, Neural machine translation, large language models, or multilingual NLP, Multimodal and
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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in foundational neural models that learn from large unlabeled image datasets, also incorporating context from additional data such as wireline logs or well reports. You are suited for this position
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should be exclusively submitted through the consortium webpage https://raptor-consortium.com/recruitment/ RAPTORplus aims at adapting proton therapy treatment with multi-modality image information acquired
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and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices. Support grant applications
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for Horticulture and Phenotyping) team research topics focus on low cost computer vision and machine learning, simulation assisted plant phenotyping and machine learning based data mining for plant biology
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Columbia (UBC) Vancouver campus invites applications for a full-time Postdoctoral Research Fellow with expertise in artificial intelligence (AI), machine learning (ML), and data science. The position will be
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intersectionality, and inclusion of underserved populations (men, students with disabilities, LGBTQ+ students, and students from immigrant communities). Excellent verbal communication skills. Interest in learning
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mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time-lapse data Proven programming expertise in