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03.06.2021, Academic staff The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and privacy-preserved
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Learning with experience in discriminative models, domain adaptation, and variational inference. Excellent analytical, technical, and problem solving skills Excellent programming skills in Python and PyTorch
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not mandatory · First experiences in the field of laser technology and data analytics are advantageous · Active interest in a commitment to the strategy of the Professorship · Determination and
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· First experiences in the field of laser technology and data analytics are advantageous · Active interest in a commitment to the strategy of the Professorship · Determination and
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data analytics frameworks (Hadoop, Spark, Flink, etc.) is desired - Interest in the development of software systems, very good knowledge and skills in programming with standard programming languages
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deep learning practical experience with software development in Python and common deep learning frameworks and libraries, experience in handling large-scale data stocks, ideally geodata, analytical
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on the 1D or analytical model) Hybrid simulation approach (e.g., which combine CFD and 1D simulations) High Performance Computing and/or GPU programming for this domain Machine learning algorithms