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test plans for process and material investigations, as well as a solid understanding of materials science. Experience in characterisation methods, particularly diffraction techniques, is an advantage
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data processing chain - from image capture, image processing/computer vision to image content analysis - using both traditional and modern machine learning and AI methods.
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to the development of prototypes and demonstrators. Under the guidance of our interdisciplinary team, you will support in research, implementing, integrating, and evaluating the latest methods in long-term secure
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"Urban Development & Mobility Transformation" focuses on researching and applying innovative tools and methods for sustainable urban development and the integrated planning of mobility systems. For our
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the lighthouse project AI Enabled Sustainable Automation, where new methods and technologies are developed to enable zero-defect manufacturing in high-pressure die-casting. In die casting, molten metal is
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the lighthouse project AI Enabled Sustainable Automation, where new methods and technologies are developed to enable zero-defect manufacturing in high-pressure die-casting. A dosing unit provides molten metal to
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the research field Power System Digitalisation, we are enthusiastically developing innovative digital solutions and methods to enable secure, flexible, interoperable, and data-driven electricity grids. Our core
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), robustness and flexibility. We cover the whole data processing chain including image capture, computational imaging and classification with classical and AI methods. You will develop concepts, specifications
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): Your qualifications as an Ingenious Partner : PhD in biology, microbiology, or other related field experience in plant microbiology / microbiome research Experience in acquisition of third-party funding
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Scientist (f/m/d) for System Transition Modelling & Policy (Full time / Part-Time: 25+ hours / week)
transformation. Your qualifications as an Ingenious Partner: PhD inrelevant social, economic, data science or related fields Interdisciplinary knowledge of transformation-oriented research, and in particular