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products to prevent, diagnose, treat, or cure disease in donors and patients. Research activities cover the full spectrum of early inventions, development into novel products and services, donor studies, and
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at the intersection of construction and digitalization: optimization of construction processes, new and alternative cementitious materials, sensor-based monitoring of concrete performance, and
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methods to automate the mechanical design process and structural validation of beams used in the ship's equipment. • Develop methods for optimizing the design of beams. • Integrate the developed methods
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research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and treatment optimization • Biomedical knowledge
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optimization of machine learning methods for processing Quantum OCT (Q-OCT) signals. Design, training, and testing of neural network architectures for artefact and dispersion removal in Fd-Q-OCT and SS-Q-OCT
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years with both research and other career-promoting work. This will be clarified in the recruitment process. A career plan will be prepared that specifies the competencies that the Research Fellow will
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institute in materials science and advanced characterization. The candidate will have access to the FastNano Liquid platform, enabling operando monitoring of PISA processes through SAXS and Raman spectroscopy
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and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from YouTube. Accept
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We invite applications for a PhD position in Efficient Edge Intelligence
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Monte-Carlo simulations to optimize the detector geometry, as well as in its testing and commissioning. It will include as well the preparation of forthcoming experiments at the DESIR facility in GANIL