189 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
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research disciplines. For further information about the different research disciplines see https://www.ntnu.edu/imf/research . Are you motivated to take a step towards a doctorate and open exciting career
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the research fields of cardiovascular biomarker research and cardio-oncology. You can find more information about the research group here: https://www.med.uio.no/klinmed/forskning/grupper/kardiovaskular-crg
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information can be found here: https://www.ntnu.edu/mai Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described above
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optimization (WOB, RPM, flow rate, etc.) using machine learning techniques Anomaly detection for downhole vibrations, bit failure, and circulation losses Integrating physical modeling, digital twins, and data
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Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
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will utilize economic theory, simulation, economic evaluation and machine learning to quantify the benefits of advanced diagnostic technologies in reducing overdiagnosis. Competence You must have
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acquisition to machine learning interpretation to 3D geometry and quality models to machine learning decision support. The PhD project will be carried out in close cooperation with Norwegian tunnelling
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within sanctioned boundaries. Underpinning both is the need for dependability models that, combined with telemetry-driven learning, can guide self-healing decisions in a way that reduces downtime without
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resilience of bridges under climate change-induced hazards such as flooding, scour, and debris impacts. The research aims to develop advanced numerical models and machine learning tools to predict loads
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and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal clubs, and research