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or machine learning frameworks Good oral and written presentation skills in a Scandinavian language at level A2 or higher Personal characteristics To complete a doctoral degree (PhD), it is important that you
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generative AI Familiar with machine-driven text mining techniques Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Highly motivated, independent and
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for more than 10 years. A comprehensive approach will be achieved through collaboration with ecologists (Applied Quantitative Ecology Group at MINA), data scientists (Machine learning at Faculty of Science and
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address this challenge using advanced experimental techniques, numerical simulations, and machine learning methods to develop high-fidelity 3D renderings of deformed samples during physical tests. By
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we will apply state-of-the-art machine learning and deep learning techniques on open- access and collected datasets to determine how accurately these systems can identify dock plants under Norwegian
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of programming/software, MATLAB, Python, OpenFOAM, LabView, ANSYS, etc. Research quality and publications – Journal papers Genuine interest in research and willingness to learn and carry out high quality research
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(AI) including predictive machine learning models, risk assessment techniques, and multi-objective optimization. The research will integrate AI-driven predictive and prescriptive approaches, focusing
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employment. Required selection criteria You must have a professionally relevant background in Artificial Intelligence, Machine Learning, and Generative AI. Your education must correspond to a five-year
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distinctions between valuable, acceptable, and non-acceptable use of these technologies in sport. The Nature and Value of Sport Virtual sports: With the help of virtual reality or computer-generated environments
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relevant education corresponding to a five-year master’s degree or a cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle