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in epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in
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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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, 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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power production), regulatory authorities, national and international research partners. Teaching Teach and further develop courses at bachelor’s, master’s, and PhD level in areas of the position
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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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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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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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(SEM), multi-level modelling, Bayesian statistics, or approaches combining quantitative data analyses with machine learning. Documented experience in teaching and related activities, such as
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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