638 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Norway
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positions are closely linked, and candidates will have the opportunity to collaborate together and learn methods from the parallel project, building a broad skillset. Both positions are part of the larger
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(NICE) Norwegian Centre for Intelligent Computers and Electronics - NTNU. https://www.ntnu.edu/nice For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294530/phd
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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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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to SAFE. Delivering EVU course from SAFE center. Required selection criteria A PhD degree (or equivalent) in biometrics, information security, computer science, electrical engineering, or machine learning
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profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and
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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 Technology » Computer technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 25 Apr 2026 - 23:59 (Europe
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the Theoretical Ecology Group (http://bio.uib.no/te ). The ocean is a physical environment that is dynamic and variable in terms of e.g. light, temperature, and ocean currents. These provide constraints and
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. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033