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- mdw - University of Music and Performing Arts Vienna
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. photoshop High-resolution confocal imaging experience Basic programming skills Excellent knowledge of Drosophila genetics Very good ability to explain research methodology and present research findings in a
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Independent research and publication activities in the field of applied mathematics Participation in existing research projects and development of new research projects in the fields mathematical image
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Responsibilities Femtosecond laser spectroscopy of molecules and aggregates inside superfluid helium nanodroplets Implementation of a Timepix3 event-based imaging detector to enable 3D momentum reconstruction Time
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position will be part of the FFG-funded research project CLAIRE. The aim of the CLAIRE project is to develop a light-weight Augmented Reality headset prototype. This will be done together with industrial
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per week) PhD-Position: Machine Learning / Medical Imaging (m/f/x) (with immediate effect). This position is offered for a duration of 3 years. Join the AICARD Research Project “Transforming Cardiac
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close-range photogrammetry (e.g., using drone and terrestrial LiDAR images) and advance the research field of photogrammetry, considering computer vision and artificial intelligence methods. Air
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experiments, as well as for its applications in medical imaging. For that, it collaborates with MedAustron, an ion cancer therapy and research center. Within this collaboration, we design and develop ultra-fast
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to express yourself both orally and in writing. • Computer literacy (MS-Office; Imaging Software). • Basic experience in academic writing. • Didactic competences / experience with e-learning
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the imperial collection (quire structure, copyists, watermarks, ruling), potentially including opera scores from other Viennese sources from the period under investigation; Ordering of digital images
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and society. Our Center for Vision, Automation & Control (VAC) is a team of approximately 140 experts carrying out applied research in image processing, sensor-data fusion, machine learning, data