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-Performance Cutting« department develops technologies and application-oriented solutions for machining along the entire process chain - from process design to real-time data acquisition for generating a
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are produced using the patented PowderMEMS technology. A core competence is the integration of porous microstructures on wafers for various microtechnological applications. Further information
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our group "Computer Vision and Machine Learning" in developing AI models and transferring them into production. In the master's thesis "Exploring latent spaces of deep networks for fault analysis in
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. As a model intercomparison project, TIPMIP brings together international modeling groups to jointly develop and run computer simulations. In this way, TIPMIP creates a unique data basis for
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analysis of existing long-term biological, chemical and physical monitoring data of German Baltic Sea coastal waters. Compilation and analysis of existing phytoplankton monitoring data with a focus on
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information about the Institute see www.leibniz-fmp.de . For questions please don’t hesitate to contact Prof. Adam Lange (alange(at)fmp-berlin.de ) How to apply: On the FMP homepage please go to
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macromolecular dynamics with machine learning, statistical mechanics, molecular simulations, and experimental data. The joint project “FAIME – Flexible and Efficient AI-driven Molecular Simulation Engine” is part
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challenges of our time. Be part of change As part of the interdisciplinary “Machine Learning Enhanced Sensor Systems” team, you will work on and develop data-driven solutions for intelligent sensor technology
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Candidates are selected by a committee of Colombian and German scientists and academics. Further information Online application: COLFUTURO Fundación para el Futuro de Colombia Carrera 15 No. 37-15 Bogotá
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and non-university research and development institutions are working together in a unique collaboration and a state-of-the-art environment to develop the data-based technologies and smart applications