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Responsibilities: Conduct individual research within the designed project: process data, develop research methods, build and evaluate computer vision and machine learning algorithms empirically. Author research
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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networks, online analysis with delay, and theory of distributed algorithms. Job description In our group, we try to apply and unite the approaches and techniques of theory and practice. Some members of our
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that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing; The design of architectures
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and/or statistical algorithms to classify building and land-use types relevant to electrical consumption Label and prepare training data for AI models; develop automated pipelines for classification
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. Prototype autonomous systems for in-space manufacturing and testing. Develop AI algorithms for navigation, guidance, and control. Lead collaborative research proposals for NSF, DoD, DOE, NASA and with other
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 26 days ago
follows a phased algorithm: 1) generate an initial training set by uniformly sampling input points 2) (re)train the model on the trainng set 3) use feedback from the model’s performance to generate/augment
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algorithms, capable of distributed learning on high performance and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence
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: Neural networks and machine learning. Algorithm. Professional Experience: In the use of Python (PyTorch, TensorFlow) and C for the development and optimization of deep learning algorithms. Experience in
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candidate should be able to conduct research work independently To learn more about the work this group does, check out the following link: https://www.nrel.gov/grid/distributed-energy-resource-management