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opportunity to contribute to cutting-edge research in statistics and machine-learning, by developing innovative methods at the interplay between theoretical and computational aspects, within a collaborative and
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task will further investigate exploitation of such methods for active motion reduction based on feedforward wave motion/load compensation in DP and crane/winch associated control systems for critical
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of Marine Technology , as part of the Norwegian Maritime AI Center (MAI) at NTNU . As a PhD candidate, you will conduct research to develop AI-driven methods for efficient methods for simulation-based testing
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several master’s programs. The faculty provides a PhD program titled Health, Function and Participation. In addition, the faculty co-manages the research area Innovation in the Public Sector in
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grade background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme . Good
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several master’s programs. The faculty provides a PhD program titled Health, Function and Participation. In addition, the faculty co-manages the research area Innovation in the Public Sector in
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Application Deadline 6 Mar 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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2026 - 23:00 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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. The project will contribute to research within human–computer interaction and human factors on topics including: human–AI teaming in safety-critical work AI transparency and explain-ability in operational
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advanced AI-enabled methods for uncertainty analysis and quantification to support high-fidelity IoE digital twins. The research will investigate approaches for identifying, modelling, and integrating