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mechanics and AI. This project will advance precision medicine through collaboration with experts in cardiology and machine learning. The mitral valve (MV) ensures one-way blood flow between the left atrium
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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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work duties after employment. Required selection criteria You must have an academically relevant background within AI, or materials-related simulations (DFT, MD, or FEM). You must have a Master's degree
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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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close relation with another PhD student in Université de Lille, France. The selected candidate will have the opportunity to learn form a consortium of 8 institutions (10 Beneficiaries, 3 Partner
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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
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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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theory (state observers, parameter identification), mathematics of partial differential equations, modelling and simulation, machine learning/reinforcement learning. Experience with design of state- and