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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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to participate in the creation of complex machines that have never existed before? Do you enjoy sharing your knowledge with younger group members? If yes, then maybe you want to work as a research assistant. The
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Are you eager to support exciting research with ultracold atoms and trapped ions? Do you want to participate in the creation of complex machines that have never existed before? Do you enjoy sharing
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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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participants Ideally, practical skills in one of (a) programming, (b) machine learning, and/or (c) design Responsibilities Developing and conducting novel research projects individually and on teams Developing a
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, and Machine Learning/AI 5G on organisations from both the private and public sectors
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approach of data-driven membrane discovery that includes material space construction and exploration, candidate selection and verification, providing data for machine learning models to optimise membrane
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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comprehensive databases combining nationwide Norwegian health and socioeconomic registry data, biobanks and patient-reported data. Using advanced epidemiological methods, causal inference and machine learning