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of Computer Science, Norwegian University of Science and Technology (NTNU). The position offers the opportunity to work on cutting-edge research at the intersection of deep learning and computer systems. The successful
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meet the requirements for admission to the faculty's doctoral programme in Engineering Cybernetics . Strong programming skills, in particular Python, and practical experience with modern machine learning
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change is transforming our oceans: reshaping wave climates, marine renewable energy potential, and coastal systems. This PhD position offers a unique opportunity to contribute to this challenge by working
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collected after a device enters the market. In this PhD project, which is part of the European COMPASS4MD project, you will study how these decisions are currently made in practice, and how uncertainty could
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multidisciplinary environments Curiosity-driven and self-motivated working attitude Knowledge of biomechanical modeling, anatomy, vision-based motion capture, machine learning, control systems Keep in mind
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considered acceptable, and under what conditions additional evidence should be collected after a device enters the market. In this PhD project, which is part of the European COMPASS4MD project, you will study
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create a sustainable world? In our multidisciplinary research team, we have a PhD vacancy in catalysts development for urea synthesis. Join our team to design and improve, in close cooperation with other
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15th October 2026 Languages English English English The Department of Structural Engineering has a vacancy for a PhD Candidate in Risk-Based Design of Protection Structures Apply for this job See
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Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 11 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through
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with European industry. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning