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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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researchers and PhD students. The research groups conduct research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as
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: simulation and risk modelling using advanced statistical and machine learning based methods. strategic portfolio management and dependency structure modelling for financial assets. effects of climate change
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communication skills in English and ability to work in interdisciplinary collaboration and in a diverse research environment. The applicant will work in a team of highly motivated PhD candidates and scientists
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and supporting PhD supervision in areas related to through-life engineering services, smart machines and autonomous systems. This position offers an excellent opportunity to work at the interface
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to contribute to the wider academic mission of the group, including supervision of MSc student projects and supporting PhD supervision in areas related to through-life engineering services, smart machines and
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quantum chemistry, experience with machine learning regression methods. Preferred start date as soon as possible but flexible. Basic Qualifications PhD in Physics, Chemistry, Materials Science, Computer
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fields. You will be an integral member of an inter-disciplinary Science of Learning research team in developing brain-based machine-learning predictive models for early identification of mathematical
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20th April 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in Fluid Mechanics Apply for this job See advertisement UiB - Knowledge that shapes society UiB shall be among
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technical support and feedback. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player