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Profile Areas Cluster of Excellence CMFI Cluster of Excellence iFIT Cluster of Excellence Machine Learning CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional
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streaming and batch processing. These efforts provide the foundation for advanced analytics, machine learning, and AI applications. The IDE Research School guides PhD researchers by offering a platform for
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
Transformation Processes. The programme is affiliated to the Faculty of Architecture, Civil Engineering and Urban Planning. Doctoral students conduct individual research in the fields of heritage conservation and
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profile: • Very good degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
researchers. The doctoral research topic, which is assigned to one of the chairs offered , also allows doctoral students to contribute their own institutional experience. A structured and international learning
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oceanography), chemistry, ecology, mathematics, computer science, engineering, economics, or political science Since the programme focuses strongly on numerical simulations, candidates with computer literacy
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professionals in industry, government, and academia. Globally, geospatial technology is often mentioned as a high-growth industry sector. Career chances for graduates with GI-related skills can therefore be
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of the brain requires the collaborative efforts of neurobiologists, neuropsychologists, cognitive scientists, medical researchers, computer scientists, mathematicians, physicists and engineers. Computational
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research