44 machine-learning "https:" "https:" "https:" "https:" "https:" PhD 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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- Western Norway University of Applied Sciences
- Norwegian University of Life Sciences (NMBU)
- UiT The Arctic University of Norway
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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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candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods
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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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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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24th April 2026 Languages English English English The Department of Mathematical Sciences has a vacancy for a PhD Candidate in Mathematical Foundations of Machine Learning for Sequential Data Apply
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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 Technology » Telecommunications technology Researcher Profile First Stage Researcher (R1) Positions PhD
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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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complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation