157 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" PhD scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
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is internationally recognized, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference
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Digital Twin for façade condition, fire safety risk classification, and maintenance planning Apply statistical and machine-learning methods to link climatic loads to degradation indicators Validate models
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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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shelf lives, and additionally may change colour, texture, and stiffness rapidly. Further, the lack of standardised 3D models for the wide variety of products makes offline learning challenging. As a
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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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Teaching and supporting of learning activities in courses related to networking Contribute to career-development activities that support your progress as an independent researcher Be prepared for changes
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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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and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal clubs, and research
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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