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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time
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either (computational) Bayesian methods, or statistical learning for complex data, unsupervised learning, or matrix factorization, is an advantage. Experience with management and analysis of large datasets
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» Autonomic computing Engineering » Maritime engineering Technology » Computer technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 25 Apr 2026 - 23:59 (Europe
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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You
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-state model will be approximated using machine-learning surrogates and will be used for a real-time optimization, such that the plant operates optimally despite disturbances. The candidate will be part of
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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, or the application of machine learning to registry data is highly valued. Experience in statistical analysis, including the use of statistical software such as STATA, R, Python, or SAS, will be viewed positively