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and verifiably safe. We consider resilience and intelligence to be part of the same process. What you will do Machine learning techniques show promising results in visual quality inspection reducing
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computational methods using network-based analysis, machine learning and dynamic modeling. We are a young, dynamic team at the idyllic Dahlem campus and teach mainly in the Computer Science, Bioinformatics and
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, and apply modern machine learning approaches yielding hybrid and reduced order models to enable real-time applications. In collaborating with industrial partners you will integrate real-world data and
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent
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few kilometers using new computer science methods, particularly machine learning. This involves the analysis of very complex spatiotemporal phenomena, especially so-called submesoscale processes
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Your Job: In this position, you will be an active part of our AI Consulting Team. Together with our partners, we develop new and innovative applications of Machine Learning. You will connect
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by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning and Data Science (MIDS) at the KU Eichstätt-Ingolstadt. The research group works at the intersection of analysis
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and verifiably safe. We consider resilience and intelligence to be part of the same process. What you will do Machine learning techniques show promising results in visual quality inspection reducing
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engage with it in the future. Qualification Required Master’s degree (or equivalent) in Computer Sciences or a related field by the beginning of the project Experience in machine learning Ability
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, conservation genomics, museomics, metagenomics, annotation, machine learning, Instruct users in the usage of hardware and software for molecular biodiversity research, Acquire substantial third-party funding