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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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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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, the details of the process are not yet fully understood. Mechanistic learning, the combination of mathematical mechanistic modelling and machine learning, enables a data-driven investigation of the processes
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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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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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THE FIELDS OF: ATMOSPHERIC PHYSICS AND CHEMISTRY, ELECTROCHEMISTRY, ELECTROCHEMICAL ENERGY STORAGE (BATTERIES), ELECTRONICS, ELECTRICAL AND MECHANICAL ENGINEERING, HIGH-PERFORMANCE COMPUTING, MACHINE LEARNING
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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for the ERC Advanced Grant project “Equilibrium Learning, Uncertainty, and Dynamics.” **Positions Available** We invite applications for Doctoral Researchers with a strong background in machine learning and an
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, storage, accessibility/sharing, archiving, publication, and preparing data for machine learning applications. The Research Training Group RTG 3120 offers, subject to the availability of resources, a
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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min