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turbulent dynamics in multiphase environments such as the ocean surface. The project is part of the Collaborative Research Centre (CRC) “Energy transfers in atmosphere and ocean” funded by the German Research
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Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference implementation of your machine learning pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with
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as well as funding acquisition and (global) outreach, if desired. International networking and collaborations are regarded as an integral part of the PhD research experience and are explicitly
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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candidate will investigate ion transport through atomically thin membranes made of 2D polymers and graphene derivatives in close collaboration with experimental partner groups MPI Halle and Leiden University
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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)physics, statistical mechanics, scientific computing and also a keen interest in interdisciplinary research and collaboration with experimental groups. You hold (or expect to complete soon) a Masters or
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this project, there will be multiple opportunities to collaborate with internal and external partners, supervise Master’s students, give oral presentations at conferences, write high-impact journal articles, as
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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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person who is eager to learn more and has a strong interest in research. Experience with membrane filtration systems (of any scale) is a definite advantage, as well as being comfortable in specifying