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. Ouyang is a physician-scientist and cardiologist with subspecialty expertise in non-invasive imaging and technical background in programming, statistics, and deep learning. As a statistician by training
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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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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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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 8 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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) enables computations to be performed directly on encrypted data without knowledge of the deciphering key, offering significant potential for privacy-preserving deep learning. However, conventional neural
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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
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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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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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(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team