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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships
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Temporary contract | 24 months | Belvaux Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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. Are you interested in applying your machine learning and deep-learning expertise to develop cutting-edge ecological and environmental research? The Senckenberg Gesellschaft für Naturforschung invites you to
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architectures, including terrestrial and non-terrestrial networks Deep learning for wireless communication problems, particularly in areas such as spectrum management, adaptive system design, or cognitive radio
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 1 hour ago
receive hands-on experience that provides an understanding of the mission, operations, and culture of the DOE. As a result, fellows will gain deep insight into the federal government's role in the creation
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foundational and applied topics in computer vision and machine learning, with particular strengths in inverse problems, generative models, and geometric deep learning. We work across diverse application areas
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view