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discipline. Desirable Experience in machine learning, deep learning, data analysis, numerical modelling, or scientific programming (such as Python, MATLAB, or R) is desirable. Knowledge of hydrodynamic
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. This project proposes the development of a new CFD simulator for offshore renewable energy applications based on physics-informed deep learning that offers greater efficiency and robustness. This is a unique and
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hours: 30.00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: 30.09.2029 Job ID: 6194 Explore and teach at the University of Vienna, where more than 7,500 academics
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sensors capable of characterizing the dynamic state of buildings and their inhabitants. By combining multi-microphone acquisition techniques with state-of-the-art machine learning methods, acoustic sensing
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
commitment to research excellence Possess the ability to work independently, take initiative, and drive research activities forward Show adaptability and a willingness to learn new concepts, techniques, and
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learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute to advancing efficient AI systems. Are you motivated to take a step
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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, as well as doctoral programmes and several Master’s programmes. Open to students in initial education as well as to professionals through lifelong learning, these programmes are delivered by our three
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) Item 03: Proven experience in both programming (Python, R, etc.) and the use of data analysis tools, as well as artificial intelligence / machine learning techniques (punctuation: 22.5) Item 04
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-content microscopy and AI/deep-learning-supported image analysis will be used to quantitatively assess neuronal morphology and maturation. Parameters will include dendrite length and branching, axon growth