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on "Development of AI Models for Capturing Connections in System Diagrams" is the development of deep learning models to capture connections in scanned diagrams. By the end of the work, a method should be
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reduction and uncertainty quantification for biological flows. The goal of the project is, in particular, the development of robust methods to quantify the propagation of domain uncertainties in
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for the research group "Immersive Media & Communication" in the department "Vision & Imaging Technologies (VIT)". In our national and European research projects, we develop new methods of interactive 3D
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consistent scientific methods for mobility planning and management, (2) integrate a new set of modular metrics for responsible mobility, (3) embed the planning methods into the open data AgiMo Digital Twin, (4
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tools? This research area sits at the intersection of Human-Computer Interaction (HCI), Artificial Intelligence (AI), and Software Engineering (SE). The goal is to design and evaluate new interaction
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founded research area of "Digital Technologies" with a focus on computer-aided high-throughput methods and AI-supported model development presentation of scientific results at international conferences and
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methods to quantify the propagation of domain uncertainties in cardiovascular simulations, especially with regard to the estimation of biomarkers for image-based diagnostics. The project is a collaboration
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computer philology also belong to the program ALT. Thus, the program is characterized by a plurality of research methods and a wide understanding of the concept of ‘a text’. Applicants are expected to have
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integration as well as multimodal data analysis should ideally incorporate user-centered methods for the participatory development of new digital health technologies in order to develop and apply patient
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for biological image data, scalable computer vision methods preparation of publications for submission to top-tier machine learning conferences contribution to teaching and/or supervision of Bachelor's and