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simulations for glass molding processes, including model setup, meshing, debugging, result extraction, and evaluation. You will also post-process simulation data in Python for optimization and machine-learning
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limited time until 31st of December 2032, available immediately Key Responsibilities: Design, implement and refine automated image analysis workflows, including machine learning–based methods
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of laser technology—is offering the opportunity to write a thesis on the topic: »AI-based local quality prediction for laser powder bed fusion«. We are currently developing machine learning-based approaches
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos.Become a part of our team and join us on our journey of research and innovation! Be
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 months ago
for use in research, film, virtual reality, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling every nuance of how humans
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physics-informed machine learning open new possibilities for establishing grid foundation models. However, it is still unclear which model structures is most capable and suitable, how well they generalize
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engineering, helping students understand how AI outputs are generated, shaped, and evaluated. To support the technical development and setup of these learning units, the research institute is hiring One Student
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project, modern machine learning (ML) methods will be developed, trained, and tested based on these real-world datasets—ideally integrated directly into ongoing plant operation. A key application example is
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approaches include data-driven parameter estimation for white-box models, the development of black-box models using machine learning methods (e.g., neural networks) and their combination (grey-box). The thesis
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Technologies are focusing on the design and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient