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) Research area: Large Language Models (LLMs), knowledge graphs (KGs), commonsense knowledge Tasks: foundational or applied research in at least one of the following areas: LLMs, KGs, knowledge extraction
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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researcher positions for projects related to photo-electro-mechanical energy harvesting systems, including material synthesis, characterization, device integration, and material simulation. The IGK2495
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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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working styles and encourage candidates who are eager to contribute to our team in a dynamic and collaborative manner. Open exchange and a supportive team environment are key to our shared success. Our
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available on site for the development of suitable radiotracers. One focus of the work is on the use and evaluation of large tomographic data sets to derive parameter data for reactive transport modeling
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available in the further tabs (e.g. “Application requirements”). Programme Description International students holding a Master’s degree in (molecular) biology, (bio-)chemistry, physics, mathematics
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Management (SLUSE) IPB: Natural Resources and Environmental Sciences (NRES) UPM: Environmental Biotechnology/Environmental Engineering/Environmental System and Modeling UGM: Planning and Management of Coastal
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. The solution relies on the integration of a biosensor into an aerosol sampler. This interdisciplinary project brings together excellent research teams from fluid dynamics, bioengineering and biotechnology. Your
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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 Germany. It offers a modern, interdisciplinary, and