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. The successful candidate will pursue an active research agenda and contribute to the Climate Policy Lab?s ongoing projects, as well as contribute deep expertise in either China, Latin America, or system dynamics
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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, applying deep domain knowledge and advanced quantitative methods to inform critical development decisions. At Northeastern University, the Fellows will engage in scientific publication, conference
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bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how
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, we believe science can achieve its fullest potential. THE ROLE During your internship you will work on a projectin the Cultural Heritage Technologies (https://www.iit.it/it/web/cultural-heritage
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Electronique, Energie, Automatique (EEA) ou équivalent. Le candidat doit posséder un bon niveau en mathématique et des connaissances en traitement du signal. Des connaissances en machine learning/deep learning
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of the following areas: Wireless and satellite communications AI/ML for dynamic networks including Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 5 hours ago
more advanced concepts such as tools for supervised/ unsupervised learning that will be helpful for deep learning focused courses. Estimated course enrolment: 35 Estimated TA support: 1 Class schedule
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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experience in machine learning and artificial intelligence who can teach in areas relevant to AI including machine learning, deep learning, natural language processing, reinforcement learning, robotics and