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topics in semiconductor technology and power electronics. The mission of the »Modelling and Artificial Intelligence« department is to optimize processes, components and systems, including their reliability
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” research hub and to contribute to taking on a globally visible leading role in the field of artificial intelligence (AI) and education in Tübingen through interdisciplinary collaboration. Possible areas
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The Fraunhofer institute for Cognitive Systems IKS is specialized on applied research in the innovative areas of artificial intelligence, cognitive systems and intelligent software architectures
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joint appointment procedure: Professorship for Simulation and Modeling of Processing Surfaces with beam-based Tools supported by Artificial Intelligence Methods (W2 with tenure track to W3 or W3
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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Future. Discover. Together. The research group "Interactive and Cognitive Systems" investigates artificial and natural cognitive systems and develops novel methods of human-machine interaction. Our
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
diversity and integrating them with knowledge on environmental characteristics. In addition to benthic communities, microorganisms in bottom waters, on manganese nodules, and artificial nodules from
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Quality”, we focus on data-driven optimization of production processes with the help of machine learning and artificial intelligence. Laser processes enable highly precise and flexible material processing
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of the consortium “DECIPHER-M: Deciphering Metastasis with Multimodal Artificial Intelligence Foundation Models”. This 5-year consortium is funded by the German Federal Ministry of Education and Research (BMBF) under
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for safety-critical applications or those requiring trust in the model. The field of Explainable Artificial Intelligence (XAI) addresses this by providing methods to make model behavior more interpretable