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responsibilities in the project. Develop digital twins of the detailed electrical power system architectures of various e-vessels based on the concept design in real-time simulation environment such as OPAL-RT and
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Position as PhD Research Fellow in formal methods for data protection in digital twins is available at the Department of Informatics. Starting date no later than December 1, 2025. The fellowship period is
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, computer science, architecture, and engineering to develop scalable, data-informed solutions in sustainable design, construction, and energy management. The Cluster aims to modernize—and ultimately revolutionize
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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devices, and edge computing platforms. Deploy machine learning models to enhance process control and system responsiveness. Collaborate with industry partners to identify research challenges, co-develop
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-erklæringen var sist oppdatert 26.07.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan inneholde
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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, which means the thesis must be submitted by the role’s starting date) in an appropriate field (e.g. architecture, civil engineering, energy, energy in buildings, community energy). PhD equivalence is
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, software development, and research experiments. Contribute to the development of working prototypes and demonstrations for mobile biometric systems utilizing federated learning architectures. Prepare
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circuit modeling, simulation, and layout design techniques. Proficiency with using relevant tools such as ADS, HFSS, Cadence and Matlab etc. Familiarity with RF/mm-wave transceiver architectures and