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- NTNU Norwegian University of Science and Technology
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Field
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methods, and structured unsupervised learning. Research Environment & Collaboration The successful candidate will work at the interface of probabilistic machine learning, computational statistics, and
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SINTEF Ocean; FME Martrans https://martrans.no/ and the Norwegian Maritime AI Centre https://www.ntnu.edu/mai The research is foreseen to focus on fluid-dynamic properties of the different sail types
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constructive and inclusive research environment. Required selection criteria You must have a relevant Master's degree in materials science, solid-state chemistry, condensed matter physics, or a closely related
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up exciting career opportunities? As a PhD candidate with us, you will work towards your doctorate in a strong international research environment and gain experience that supports a future career in higher
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the environment, food production and sustainability. The aim is to generate new knowledge of the sustainable management of biological resources. Read more about the PhD program here . The workplace is at Campus
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Department of Computer Science at the Norwegian University of Science and Technology. The department is an active and dynamic environment for cutting edge research in all areas of computer science ranging from
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an understanding of the interaction between human operators, technology and operational conditions. The project must maintain a clear connection to maritime operational technology and operational environments
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Range (NCR). The research aims to investigate how cascading cyber effects can be represented and executed across interconnected digital environments, including both IT and Operational Technology (OT
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methods, and structured unsupervised learning. Research Environment & Collaboration The successful candidate will work at the interface of probabilistic machine learning, computational statistics, and
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learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute to advancing efficient AI systems. Are you motivated to take a step