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the project/work tasks: Advanced data management on large datasets to facilitate data for statistical analyses Design and plan analyses Make efficient analysis pipe-lines in the statistical software R
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School of Public Health i Boston with Associate Professor Jannicke Igland as local principal investigator at the University of Bergen About the project/work tasks: Advanced data management on large
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30 PhD and post-doctoral fellows, and a large number of master’s students. About the PhD project: The goal of the project is to develop a simulation tool that, based on meterological and map data, can
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thermal imaging data, and potential clinical and signal data, to create algorithms capable of recognizing key clinical activities and interventions. Building on recent advances in computer vision and
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, which has 15 permanent staff members, is responsible for the bachelor's, master's, and PhD programs. The department also has a large portfolio within continuing and further education (EVU). Furthermore
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on advanced statistical methods for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological, and environmental factors contribute to severe mental and
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for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological, and environmental factors contribute to severe mental and neuropsychiatric disorders
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to develop methodologies for real-time modeling and inversion of geophysical well logs, with a particular focus on borehole electromagnetic data during drilling. This includes the further development
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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages
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climate change are far-reaching, particularly when it comes to identifying and interpreting trends in regional-to-local scale signals and extreme events. Large ensembles of climate simulations are a key