82 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation" "St" PhD positions at DAAD
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Dresden, Germany, Technische Universität Dresden and the University of St Andrews, Scotland. By working together, we create a highly attractive overall package of PhD level research on solid-state chemistry
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Description The Research Training Group (in German: Graduiertenkolleg, GRK) RTG2670 “Beyond Amphiphilicity: Self-Organization of Soft Matter Via Multiple Noncovalent Interactions” in the second
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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expertise and supervision of experienced researchers from multiple institutes at Forschungszentrum Jülich. As one of Europe’s largest and most multidisciplinary research centers, Forschungszentrum Jülich
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methods for photocatalytic membrane development. The project will focus on i) photocatalyst selection, looking beyond the most commonly used materials, ii) exploring options of catalyst deposition and
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compounds, etc. The project will focus on the i) development of membrane filtration systems and operation with novel nanofiltration membranes, ii) examination of the physical/chemical processes inside
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research and development, including; Feasibility studies on contaminant removal in a solar powered electrodialysis process Establishment of the most suitable energy management scenario in collaboration with
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders