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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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computer science, or a field related to computational sciences. Must have a strong background in computer vision, artificial intelligence (AI), and/or wireless networking and systems, and related fields. Preferred
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vehicle validation. Design and implement machine learning models that capture the complexity and variability of real-world traffic situations, including unusual pedestrian behaviors, edge cases, and multi
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description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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research, covering research topics including, but not limited to Crop Modeling, Machine Learning, Artificial Intelligence (AI), Internet of Things, and Big Data analysis for Precision and Prescriptive
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of machine learning and decisions applied in cooling systems as per
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on Earth. We have computational capabilities that are designed to process millions of tasks in parallel, allowing the entire body to function under extremely variable conditions. Our organ of vision
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of Acoustic Sensing and Machine Learning for Sustainable Battery