45 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" scholarships at NTNU Norwegian University of Science and Technology
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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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. 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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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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» 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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combined with competitive knowledge and skills. The Department of Civil and Environmental Engineering is one of eight departments in the Faculty of Engineering. Where to apply Website https
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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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. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning engines, and reinforcement learning—can be adapted and extended for maritime design
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area on civil security by focusing on the vulnerability assessment of urban environments, sustainability, resilience, and knowledge for a better world (https://www.ntnu.edu/civil-security ). Duties
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(s) Number of offers available1Company/InstituteDepartment of Computer ScienceCountryNorwayCityGjøvikPostal Code2815StreetTeknologivegen 22Geofield Contact City Gjøvik Website http://www.ntnu.no Street
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the semantic foundation that enables AI systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI