211 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" scholarships in Norway
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Experience with AI / probabilistic AI / Machine Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Experience with predictive maintenance, fatigue, fault detection
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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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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling
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practical information about working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted
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research or project activities involving machine learning or data-driven modelling you demonstrate knowledge of energy systems, smart grids, or cyber-physical systems Personal characteristics To complete a
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/ ). By combining advanced machine learning techniques with qualitative methods, the project will investigate usage patterns and engagement levels with a health app across multiple European countries
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/ ). By combining advanced machine learning techniques with qualitative methods, the project will investigate usage patterns and engagement levels with a health app across multiple European countries
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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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inquiries, please contact hrtkd@oslomet.no Deadline for application: May 4th, 2026 Ref: 26/06383 Where to apply Website https://academicpositions.com/ad/oslo-metropolitan-university/2026/phd-fellow-i