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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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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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theory (state observers, parameter identification), mathematics of partial differential equations, modelling and simulation, machine learning/reinforcement learning. Experience with design of state- and
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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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using machine learning or any other AI technique. Knowledge of CCS. Good oral and written presentation skills in Norwegian/Scandinavian language equivalent level B2. Personal characteristics To complete a
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to your work duties after employment. Required selection criteria You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining, with a research
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criteria Prior publications within relevant fields Strong problem-solving skills and a demonstrated capacity for innovative thinking Experience and expertise in machine learning Personal characteristics