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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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to the success of the whole institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Robotics offers a position as Research Associate / PostDoc (m/f
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Development effective at the earliest possible date: W1 Professorship in Machine Learning in Agricultural and Food Economics (f/m/d) The professorship will initially be awarded with civil servant status for a
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using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering
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of the science location Cottbus-Senftenberg and increase its visibility. Through innovative research and new teaching and learning formats, the BTU is shaping the future: with scientific findings and practice
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used
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Behavior Models (NBM), fault detection methods, and other operational analytics based on operational data from WTs. You will apply machine learning techniques and incorporate your understanding of wind
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microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
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Your Job: In this position, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting