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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Personal characteristics Ability to work independently and in a team Drive to learn new methods and applications
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need, this may be prepared from published field operation data, laboratory measurement or other sources. Machine learning can be used to select the bet data set for each particular cases covering
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the interaction between digitalisation and society from various theoretical perspectives and develop new responsible digital technology. Our other priority area of research is Language in Learning, which aims
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A Doctoral Research Fellowship in Machine Learning for Critical Healthcare is available at the Faculty of Computer Sciences, Engineering and Economics at Østfold University College (ØUC). The research
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for changes to your work duties after employment. Required selection criteria You must have an academically relevant background within Learning Technologies, Interaction Design, Human-Computer Interaction (HCI
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-driven or machine learning techniques relevant to structural engineering Experience with wind energy infrastructure through education or work Personal characteristics To complete a doctoral degree (PhD
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efforts to contribute to safer marine operations, we actively explore possibilities to utilize both numerical and machine learning methods to enhance the accuracy and resolution of metocean forecasts. About
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foundation for theory-guided catalyst design e. g. by machine learning approaches. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within
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sciences Economic and Administrative sciences Maritime sciences Social sciences and Humanities. The Faculty is also responsible for PhD programmes in computer technology, innovation and regional development
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water