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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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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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development and deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is designed to achieve the following
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. Successful and rapid development and deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is designed
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deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is designed to achieve the following training
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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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under current conditions and with respect to global change scenarios. Embedded into the inspiring academic environment of IGB and the Universität of Hamburg, RTG 2530 provides Doctoral and Postdoctoral
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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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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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. Only online applications will be accepted. AVAILABLE PROJECTS: Nanoscience: Application of bistable DNA devices Nanoscience: Synthesis of Carbon-Nanostructures on Inert Surfaces Biophysics: Learning