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approaches to remove atmospheric particulate (e.g., PM2.5) pollution. The math-based subgroup focuses on the use of deep learning and generative AI to address critical problems for the electric grid and broad
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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are the lead technicians for all events that occur at The O'Shaughnessy. While each employee may be assigned to a specific specialized area of the production department, general knowledge and deep skills in all
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Macomb Community College teaching Faculty demonstrate deep subject matter knowledge and provide effective instruction to students using various modalities including, but not limited to, on campus, online
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 6 days ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable
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: Required: • MSc (or equivalent) in: Computer Science, Cybersecurity, Machine Learning, or related field • Strong background in: machine learning / deep learning, mathematics (probability, linear algebra
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learning and deep learning models for renewable energy forecasting, particularly wind power generation. Working with data-driven weather prediction models and high-resolution meteorological datasets
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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the development, evaluation, and practical application of machine learning methods (especially deep learning) Publication of scientific results in renowned international journals and conferences Teaching of courses
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, computer science, data science, or similar · Strong publication record in peer-reviewed conferences and/or journals · Experience applying machine learning methods (especially deep neural network approaches