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– from the modeling of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference
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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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an amount of 1,575 EUR per month. For expenses directly related to the doctoral project (e.g. learning materials, travel), an additional subsidy may be granted on submission of receipts. Application Papers
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. Only online applications will be accepted. AVAILABLE PROJECTS: Nanoscience: Application of bistable DNA devices Nanoscience: Synthesis of Carbon-Nanostructures on Inert Surfaces Biophysics: Learning
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learning approaches. A central aspect of this project is the formation of a complex sorption layer—known as the eco-corona—on the nanoparticles and its influence on pollutant sorption. We are seeking to hire
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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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. Only online applications will be accepted. AVAILABLE PROJECTS: Nanoscience: Application of bistable DNA devices Biophysics: Learning in living adaptive networks Biophysics: High-resolution structural
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missions. Prior experience with methods of statistical inference using simulations or anomaly searches with machine-learning approaches is desirable.
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challenges, the school provides a wide variety of topics, from logic in autonomous cyber-physical systems to machine learning in Earth System models. You will have one supervisor from the mathematical sciences
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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