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team will be located within a rewarding professional environment with an active community of PhD candidates and postdocs. Duties of the position As a PhD fellow, you will be expected to: Develop your own
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systems such as fuel cells and batteries. Intelligent control and management systems will be designed to enhance efficiency, sustainability, and seamless integration. Developed models and strategies will be
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Additional preferred expertise and experience Experience with longitudinal data analysis and advanced statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural
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of Biostatistics, Institute of Basic Medical Sciences (IMB), University of Oslo (UiO), Norway. The candidate shall take part in the research group on “Statistical models for high-dimensional and functional data
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project “ComDisp: Community-Centered Modeling of Housing-Related Health Disparities.” ComDisp develops a grassroots modeling framework to predict health disparities under different climate change scenarios
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/work tasks: The position is part of the Belmont Forum project “ComDisp: Community-Centered Modeling of Housing-Related Health Disparities.” ComDisp develops a grassroots modeling framework to predict
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biodiversity. Specifically, the primary focus of the PhD will be to analyse and parameterize models describing the ecological and evolutionary dynamics of small and fragmented populations, and how the risk of
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statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural equation modeling). Familiarity with the opioid and endocannabinoid system and topics related
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they release their toxic cargo to kill the cancer cells. Methods include, but are not limited to, in vitro culture of primary human cells and cell lines, organ-on-chip models, molecular biology, diverse
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acceptance of new products and business models. Immersive media technologies (IMT), such as Virtual Reality and Augmented Reality, may play an important role in exploring consumer behavior, and also represent