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mathematical frameworks for multimodal integration, advance video transformer architectures for temporal-spatial dynamics, and develop few-shot learning methodologies for ultra-low-resource scenarios with only
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
with Computer Vision and Deep Learning architectures (CNNs, RNNs, etc). Strong foundation in machine learning and data science. Programming skills with proficiency in Python, Java, and/or R. Preferred
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sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific excellence as a basis
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and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable
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develop the first fault-tolerant quantum computers that can handle applications at realistic scales. To date, several architectures for quantum hardware have been developed that all have their strengths and
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Description: Design and Implement Hybrid Data Architecture: Evaluate, configure, and manage cloud-native data warehouses for scalable spatial analytics Design data flows from warehouse to spatial databases
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and natural sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific
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scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and
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: Design and implement AI/ML pipelines for multi-omics data integration, including supervised and unsupervised learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph
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algebra methods targeting large-scale HPC systems. Optimization of linear algebra libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications