21 machine-learning-phd PhD positions at NTNU Norwegian University of Science and Technology
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analysis and/or advanced algebra or algebraic topology. Knowledge and experience of machine learning. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work
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on the problem of making distributed machine learning robust to network outages and computational bottlenecks. The work is part of the Norwegian national AI centre SURE-AI, and the PhD student will
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Computer science » Computer systems Computer science » Programming Technology » Communication technology Technology » Telecommunications technology Researcher Profile First Stage Researcher (R1) Positions PhD
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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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Computer science » Computer systems Computer science » Programming Technology » Communication technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr 2026 - 23
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» Autonomic computing Engineering » Maritime engineering Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 18 Apr 2026 - 23:59
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seeking a PhD candidate in computer architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators
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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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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