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writing. • Computer literacy (MS-Office; Imaging Software). • Basic experience in academic writing. • Didactic competences / experience with e-learning. • Excellent command of written and spoken
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in software development, and keen interest in dynamics of stellar systems. A key task is to lead the development and support applications of our pioneering code for orbital modelling of stellar systems
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cloud data using state-of-the-art techniques (e.g., image processing, machine learning) A significant fraction of the work will be focused on the maintenance and strategic development of the group's
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to be coupled to model-free analysis of molecular dynamics simulations. This includes work in the biochemical wet-lab as well as with prototype NMR spectroscopy and computational tasks. You have previous
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analyze three-dimensional motion capture data and medical images from various groups, including clinical populations, healthy people and elite athletes. Our goal is to improve clinical decision making in
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, conference presentations) A statement from your supervisor committing to support your finalization phase Compliance with the CoBeNe regulations for PhD candidates (agreement to the Code of Good Practice, FÖP
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Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data’ as Data Manager. Work alongside leading experts at the Computational Imaging Research Lab (CIR ) and the Department
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research methods Experience with image editing programmes What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely. Inspiring working atmosphere: You are a
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Machine Learning, Code Analysis/Generation for Machine Learning and MLOps, and Continuous Delivery and/or MLOps. You participate in research projects and studies. You hold university courses within
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. The team's research interests focus on works, media, and contexts of images, architecture, and objects of Islamic art and the early historiography of Islamic art. Current research explores Arabic, Persian, and