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international and dynamic team of researchers investigating problems in information retrieval (IR) and natural language processing (NLP) and their applications to health and medicine. The successful candidate
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reconstruction to overcome these challenges. Your tasks - develop physics-informed, self-supervised learning approaches for phase retrieval - implement reconstruction algorithms on HPC clusters for large-scale
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tomography and local adaptive reconstruction to overcome these challenges. Your tasks develop physics-informed, self-supervised learning approaches for phase retrieval implement reconstruction algorithms
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g
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arrival date of the university central mail service or the time stamp on the email server of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a
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incorporating data on resource productivity, innovative extraction methods, and social acceptance. For this you will work together with project partners to retrieve real world techno-economic data as a foundation
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understand microbial life and the ways in which it affects our biosphere. MarMic students are trained to think globally and to choose from both holistic and reductionistic research approaches. The breadth
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extraction methods, and social acceptance. For this you will work together with project partners to retrieve real world techno-economic data as a foundation for integrating geothermal plants into European
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elements Application deadline The application deadline for admission to the winter semester is the end of February each year. The exact dates can be found on our website: https://www.sozphil.uni-leipzig.de
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within the faculty participate in the programme. The course content is very broad and the specific subject of the dissertation depends on the institute. For research subjects, please see our website: http