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Field
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research group has a long standing interest in integration of multi-modal data, in which you will also receive training from a senior colleague. The opportunity to develop Digital Twin projects are also open
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of optics, imaging systems, digital holography, speckle metrology, Matlab and simulations, signal processing, the Fourier transform, machine learning, and classifiers such as SVM. Meriting qualifications
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benefiting from the ongoing digitalization of society. Our research emphasizes social, economic, and environmental sustainability. As a postdoc, you will become part of a dynamic team that offers a stimulating
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their own research agenda within some of the department’s core themes: Digital transformation and innovation strategy – how organizations adapt their innovation processes and strategic priorities in response
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areas is considered a merit: - Multi-modal data processing for decision-making in natural environments - Terrain classification and multi-layered environment mapping - Digital twin generation for natural
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climate benefits throughout the life cycle. Research is ongoing in many disciplines such as forest management, forest economics, forest ecology, digitalization of forestry, forest damage, forest soil
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to be revalued. The project studies the processes through which value transformations of bio-waste are made. Examples of wastes that might be of interest are wastewater, stormwater or forest waste. The
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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under important documents below the ad. The credentials you invoke must be verified with certification and they must be attached digitally in your application. Other documents, including various types
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing