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given to applicants with: Hands-on experience with digital twin simulation platforms, edge computing, and smart factory infrastructure. Background in data acquisition, signal processing, or real-time
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properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 17th August 2025 Languages English English English PhD Research Fellow in Formal Methods for Data Protection in Digital
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of public law wih direct links to international law. Of particular interest are applicants who are interested in the Asia-Pacific region; technology and digital economy; sustainable development; cybersecurity
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of predictive AI models using multimodal data (e.g. time-series signals, neuroimaging, clinical records) for healthcare applications. Contribute to the development of a Digital Twin of the brain's motor system
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are a major part in implementing the 2030 vision of the Faculty of Medicine, i.e. to become leading within digital health and well-known for doctors and engineers finding solutions together. Our mission
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Computer Science, Electrical & Electronic Engineering, or equivalent. Background knowledge in signal representation/processing, data-driven and machine learning/analysis, esp in climate related topics. Prior
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to international law. We particularly seek candidates focusing on the Asia-Pacific region, technology and the digital economy, sustainable development, cybersecurity, international economic law, and international
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wearable devices using digital knitting and advanced fabrication techniques. Motion Sensing & Data Processing: Implement and optimize algorithms for joint motion tracking, integrating signal processing and
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robotics, cybersecurity, sensing and signal processing, smart mobility and energy systems. In addition, they are using their expertise in interdisciplinary research initiatives across the university. We
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provides: (1) opportunities for publication; (2) the chance to develop knowledge and skills in neuroimaging analysis; and (3) experience of working with digital mental health and smartphone-based assessment