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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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ethnomycology or ethnobiology large-scale (ethnographic) database construction phylogenetic comparative analyses with Bayesian computational tools The applicant must have the ability to work independently and in
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competence in seismic data analysis is a requirement. Experience from or competence in computer programming (MATLAB, Python) is an advantage. Applicants must be able to work independently and in a structured
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a requirement. Experience from or competence in computer programming (MATLAB, Python) is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good
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snow in local and regional climate models is poorly constrained, leading to uncertainties in estimating mass loss through sublimation and snow redistribution. The PhD candidate will develop and execute
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estimating mass loss through sublimation and snow redistribution. The PhD candidate will develop and execute a field campaign focused on observing the role of blowing snow on sublimation and redistribution
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8 Sep 2025 Job Information Organisation/Company University of Bergen Department Geophysical Institute Research Field Engineering » Computer engineering Physics » Metrology Physics Researcher Profile
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master's students, and contribute to the dissemination of research findings. Work closely with computer scientists, statisticians, and neurologists to ensure both clinical relevance and methodological
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with other researchers, perform data analyses, write scientific articles, supervise master's students, and contribute to the dissemination of research findings. Work closely with computer scientists