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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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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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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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, their achievements and productivity to the success of the whole institution. At the Faculty of Mechanical Science and Engineering, Institute of Manufacturing, the Chair of Forming and Machining Technology is offering
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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