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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking a science manager for its new center for Machine Learning in Earth Observation (ML4Earth
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Learning in Earth Observation (ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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of interest include, but are not limited to: AI methods that meet the complexity of living systems, high-dimensional machine learning for biology, statistical machine learning, AI‑driven laboratory automation
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Max Planck Institute of Molecular Cell Biology and Genetics | Dresden, Sachsen | Germany | about 24 hours ago
: Dresden, Saxony 01307, Germany [map ] Subject Areas: Artificial Intelligence, Machine Learning, Applied Mathematics, Biomathematics, Mathematical Biology, Computational Science, Statistics, Numerical
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established that reliably identifies the connected components in the diagrams. You will learn about novel AI models and exchange ideas with experts from the building sector. The "Image Processing and Machine
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contribution of genetic and non-genetic driving forces for the cells’ evolution and glioma development. Using multi-omics data integration and machine learning, we will investigate cellular behaviors and gene
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neural simulators (NEST, Brian, etc.) and/or machine learning frameworks (PyTorch, Tensorflow, etc.) is a plus Experience with spiking neural networks and/or neuromorphic computing is a plus Please feel
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community around machine learning of the SCADS.AI center (https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change Era. We aim to attract the best
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from the vibrant research community around machine learning of the SCADS.AI center ( https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change