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. This project focuses on advancing the TechDB database with AI-driven automated data collection, developing methods and tools for integrating heterogeneous data into multi-energy system design and operation, and
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assessment, you will develop new, sample-efficient optimal control approaches for gate calibration and test them in numerical simulations. You will pursue your research with the German research collaboration
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smart grid). While there has been tremendous progress in formal verification of cyber-physical systems, existing approaches still require expert knowledge. The main goal of this project is to develop
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, we make concrete contributions to achieving the 17 Sustainable Development Goals (SDGs) of the United Nations. Our employees conduct research in the fields of energy, environment, safety, health
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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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Are you ready to develop and implement the latest Reinforcement Learning approaches? At the Fraunhofer Application Center for "Connected Mobility and Infrastructure" in Ingolstadt, a unique
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data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop control algorithms to enhance grid
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efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further
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with OSL: Use OSL to implement the PPTBF algorithm in 3D environments: like a couple of point process, feature function and window function. Optimize Procedural Algorithms: Develop more efficient methods
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: • Mathematical derivation, analysis, and comparison of models, methods, and simulation approaches. • Rapid prototyping of new ideas in custom code. • Implementation of new models, methods, and algorithms