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, training deep learning models to adapt designs to boundary conditions, and integrating FEM workflows within parametric modeling environments like Grasshopper. The candidate will contribute to building a
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and written communication skills in English Experience with relevant deep learning and machine learning methods An interest in the biomechanics of human motion Colourbox via Unsplash Colourbox Personal
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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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deep interaction with nature. Core questions concern how current and potential future sport relate to requirements on sustainable development and ecological values. Human Movement Skills: Epistemological
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. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data frameworks
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-optical frequency division scheme. The successful candidate requires a deep knowledge of optical microcomb and integrated photonis as well as strong grasp of RF technology and microwave oscillators
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experiences and skills will be emphasized: Desired knowledge/experiences in: Working with diverse remote sensing data Data science topics particularly machine learning and deep learning. High Performance