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control and optimization of electrolysis from the cell to the stack requires automated monitoring, analysis, and control of the operating parameters and processes. As part of this project, the potential
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 7 days ago
develop our state-of-the-art imaging systems by optimizing the hardware and integrating real-time data processing and analysis through machine learning techniques to achieve precise characterization
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on the recently published DeepRVAT framework, which leverages advances in machine learning to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend
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Broadband UV-generation position Push the frontiers of nonlinear optics in multi-pass cells Optimize third harmonic generation in nonlinear gases Develop scaling concepts to kJ pulse energy levels General
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using DC and AC-based techniques such as characteristic curves, cyclic voltammetry and electrochemical impedance spectroscopy Participation in the investigation of stacks and cells post-test using
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of fluid dynamic modeling and the analysis of thermomechanical stresses, you will accompany the entire development process – from the optimization of electrochemical performance to the elaboration
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exchange and interaction state of the art computing infrastructure (HPC) salary assigned according to the pay scale UKF standard social benefits, e.g. UKF job ticket UKF Your tasks: develop and optimize
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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analysis, simulation, chemometrics, control engineering, artificial intelligence, soft sensors, and process sensors. We are always looking for new technologies and new methods to monitor and optimize