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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 7 hours ago
cooperates closely with all faculties , the BTU Research Department, and the BTU Welcome Centre . Qualification Programme: In addition to your independent research, the GRS also offers you a comprehensive
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selection criteria You must have an academically relevant background within Civil / Environmental / Hydraulic Engineering, Computer Science, Applied Mathematics, or related areas. You must have a Master's
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to the empirical nature of the project or at least reached within 2 years after starting the PhD program. We are looking for you who are independent, self-driven, and analytical, with an ability to manage complex
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, you will leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modeling systems as graphs and encoding nonlinearities in these. As
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review or select your application. Knowledge/Skills/Abilities: Sufficient relevant experience to contribute significantly to a specific project. Experience with the use of computers and other appropriate
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resulted in many models of limited effectiveness. This project proses to take a Systems Architecture and Systems Engineering approach to neuropathic pain. Systems Architecture and Engineering is used
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-throughput datasets generation and analysis, prediction of microfluidic architecture performance, or guided device design. Condition of Employment Reliability Status Language Requirements English Note
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16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant
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of specialization include: Web Application Engineering Model-based Systems Engineering AI for Software Engineering Software Engineering for ML Big Data Architectures Cloud Architectures Contribution to Software
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architectures which leverage our increasing understanding of the behaviour of neural networks trained with DP to ameliorate these trade-offs in biomedical applications. - Foundations of private machine learning