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design of complex physical systems. The group is jointly embedded at Saarland University and DFKI in Saarbrücken. Current Research Directions include: AI for scientific computing – neural operators and
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users applying our methods. We want you to understand what they need, identify where current workflows fail them, and build better ones. This position comes with unusual freedom and ownership. We want you
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Learning at TUM works on machine learning, artificial intelligence, and information processing, with a current focus on foundation models, data-centric research, and applications to scientific and medical
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applications, spreadsheets, and data management tools. Ability to work independently while contributing effectively to a multidisciplinary research team. Preferred Qualifications Experience coordinating
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firmly established, the processes of transport and burial during turbidity current events remain poorly understood. The DEEP-FLUX project aims to establish a new physical framework for quantifying fluxes
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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-of-the-art machine learning methods, acoustic sensing can provide valuable insight into a wide range of processes occurring within the built environment. Potential applications include structural health
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autonomous systems, robotics, flexible asset (e.g., storage, electric vehicles) management in smart grids, etc. You will publish scientific articles related to the research project. You will carry out a
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-stationarity. Potential application domains include autonomous systems, robotics, flexible asset (e.g., storage, electric vehicles) management in smart grids, etc. You will publish scientific articles related
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11 Jul 2026 Job Information Organisation/Company University of Antwerp Research Field Computer science » Other Engineering » Communication engineering Engineering » Electrical engineering