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Field
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the amount of tedious and error-prone manual work. The driving factor is the availability of large amounts of data. However, in this domain data is often sparse or labelling data is expensive. This requires
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contributions to mastering the global challenges of mankind in the fields of energy, mobility, and information. For this, about 10,000 employees of KIT cooperate in a broad range of disciplines in research
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of climate services. RIVIERADE will target three European Seas (Baltic, Black, Mediterranean), to produce data and information for ocean health, sustainable blue economy, and coastal climate risks
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system development and software development for four scientific laboratories Measuring devices and data analysis • InSAR (Interferometry of Synthetic Aperture Radar) computing system • IR mass spectrometer
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using experimental data from laboratory setups Validate models through targeted measurements and structured testing procedures Analyse loss mechanisms and system efficiencies under various operating
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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environment of the institute. Opportunities Access to a unique and comprehensive dataset combining genomic and clinical information from a large cohort of cancer patients. Potential to establish an independent
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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Technomathematics, computer science, engineering, physics, mathematics or natural science or equivalent degree Very good knowledge of techniques and methods of computer-aided sciences Knowledge and experience in