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socioeconomic registry data, biobanks and patient-reported data. Using advanced epidemiological methods, causal inference and machine learning techniques, we aim to: Improve understanding of risk factors for
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, interaction design, Human-Computer Interaction, human-centred AI, UX research, immersive or interactive media, and other related areas. Teach and supervise topics in the Bachelor’s and Master’s programmes in
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Further develop existing courses or develop new courses and learning formats in human-machine interaction, human-centred design and the design of safety-critical systems Conduct research at a high
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, specialising in either machine learning or quantum information science. The Department of Information Theory at Simula UiB conducts research on two main areas: statistical learning theory and quantum information
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and Electric Machines research group (PEM), which is one of four research groups in the department. The main responsibility of the Professor/Associate Professor will be research and teaching within
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, advanced imaging, AI/machine-learning approaches, mathematical modelling, or novel computational methods are especially welcome. The successful candidate will receive a competitive start-up package and join
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insights. Ability to apply system-level thinking, linking infrastructure performance, environmental conditions, and operations. Experience with data-driven modelling or machine learning. Ability to work both
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using both manual and machine learning techniques Generating new data through GIS, web scraping, and text analysis Performing data analyses and literature reviews Project management, including
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with researchers in epidemiology, biostatistics, informatics, machine learning, artificial intelligence and precision medicine. The Department leads the UiO:Real-World Evidence (UiO:RWE) convergence
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. Theoretical activities include research on quantum information theory, quantum algorithms, quantum engineering, many-body theories for quantum technologies, quantum machine learning, and fundamental quantum