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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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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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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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on ROS2 (Robot Operating System) and best practice of use of Github. Knowledge and skills on methods in numerical optimization, machine learning, as well as knowledge on marine power and control systems
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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