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11.07.2022, Wissenschaftliches Personal The professorship “Big Geospatial Data Management” is seeking to fill two research assistant (E13) positions to support research activities around geospatial
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interoperable methodological framework for AI in gynecological oncology. We integrate symbolic knowledge representation (Ontologies/Knowledge Graphs) with Retrieval-Augmented Generation (RAG) and Large Language
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requirements are Experience in working with large-scale spatial-temporal traffic and/or travel behavior data, e.g., loop detector, floating car data, GPS data, cellphone data. Experience with transport
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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processes, and the application of AI methods in engineering. Description: Nowadays, computer-aided manufacturing (CAM) methods are used to a large extent for the production of complex machine components, in
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models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio
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conditions, to large field-scale experiments with wild and domestic grazers. These experiments will test hypotheses related to the effects on nutrient cycling of grazers with different body size and grazing
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to design and conduct experiments at various scales from laboratory manipulations of animal plant-soil systems including micro and mesocosms under varying environmental conditions, to large field-scale
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to the research and development of dexterous end effectors for a new 6G-based teleoperated surgical robotics system. This position stems out of the large scale 6G-Life project (https://6g-life.de/) and will give