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Field
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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in our team. Learn more about us here: https://sc.cs.univie.ac.at/ Your future tasks: Active participation in research, teaching and administration, which means: You develop your independent research
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developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party
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breakthrough and to contribute to the welfare of society and humanity through developing innovative technologies. We also conduct research on ethical, legal and social issues caused by the spread of AI
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application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
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/or observationally motivated model-building for SMBH feeding and feedback. The group integrates observations, theory, data analysis, algorithm development, model-building, and numerical simulations
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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, complex systems. Strong communication and writing skills; ability to work both independently and as part of a team. About the team The DATA team develops foundational mathematical and algorithmic approaches