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networks, computer science or equivalent, with a strong background on theoretical and applied ML/AI. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained
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science » 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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science, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning
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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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applicants should have a strong academic record with a solid background in Machine Learning. Knowledge of Vision-Language-Action models and Novel View Synthesis techniques is a strong plus. Good programming
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» Computer engineering Engineering » Electrical engineering Engineering » Other Technology » Telecommunications technology Researcher Profile First Stage Researcher (R1) Application Deadline 23 Apr 2026 - 21
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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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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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for energy management and decarbonization. Vision We are seeking a PhD student that is motivated and passionate about the design and control of power electronics technologies that make real-world impact
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, robotics, and machine learning. You will work within a multidisciplinary supervisory team spanning engineering, robotics, and computer science, and collaborate with researchers working on real-world