96 learning-"https:"-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" positions in Finland
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teach and supervise theses at Master’s level (https://www.helsinki.fi/en/degree-programmes/nutrition-science-masters-programme and take part in the supervision of doctoral and post-doctoral researchers
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conducting research at Hanken to apply for Marie Skłodowska-Curie Postdoctoral Fellowships. Marie Skłodowska-Curie Postdoctoral Fellowships (MSCA PF) target researchers holding a PhD who wish to acquire new
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related field. Strong knowledge of machine learning. Strong publication record in a relevant field. Excellent analytical and problem-solving skills. Interest in collaborative research with both academia and
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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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financial markets and allows you to learn many aspects from fundamental research problems to concrete applications. More information about the research teams can be found from the centers’ web site: https
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collegial work environment, and continued commitment to your support, learning, training, and development. For further information about the position, please contact Samuli Honkapuro, professor, either by
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recognised as having a significant influence on their field. For more information on the tenure track model and the assessment criteria, please see https://www.helsinki.fi/en/about-us/careers/academic-careers
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of Management Studies at Aalto University School of Business (http://management.aalto.fi ). The department comprises several highly competitive research groups in organization and management theory, strategy
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be exempted from the Swedish requirement. The employer will support the appointee’s language learning. Read more about the language requirements: https://www.helsinki.fi/en/faculty-educational-sciences
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growth and yield studies. Knowledge of different digital data collection tools, statistical approaches, machine learning and AI-based techniques, forest growth modelling and simulation systems, as