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Field
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validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE’s SWARM project (https://swarm-workflows.org
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will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest management communities. Engage with industry
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techniques to develop computational algorithms and statistical methods that find patterns and relationships in large volumes of data. Manage, collect, visualize, analyze, and summarize data, data reports
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. Responsibilities Design, implement, and assess advanced underwater acoustic modeling techniques and algorithm development across various disciplines such as signal processing, statistical inference, propagation
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, Databases, etc.), Machine Learning, Theoretical Computer Science (Discrete Mathematics, Algorithms, etc.). Experience with EdTech tools, such as Ed Discussion, Gradescope, GitHub Classroom, Canvas, etc
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and methodological perspective of an engineer. Students build advanced design and engineering skills, enhance their knowledge in cloud computing, and develop machine learning algorithms. With a passion
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to achieve the following objectives: 1. Characterize 3-D Urban Structure and Change: Utilize data from multiple remote-sensing platforms and deep learning algorithms to generate high-resolution maps of 3-D
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change how we explore space by developing innovative theories, algorithms, and technologies. Position is contingent upon availability of funds and proper Visa paperwork, to be able to work in US. Position
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will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest management communities. Engage with industry
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing