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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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Degree Doctorate Course location Potsdam In cooperation with The innovative PhD and postdoctoral scholarship programme is offered in conjunction with the Faculty of Digital Engineering, a faculty
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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) engineering, computer science, or a related field You have very good knowledge of energy technology, energy economics, and energy policy You have already gained initial experience in energy system modeling You
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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xenograft (PDX) models. To this end, the candidate will have direct access to cutting-edge mass spectrometry and advanced bioinformatics infrastructure. The project is part of the collaborative research
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains