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–time modelling in GIS and/or statistical software (e.g. R) to visualize and analyze the spread and control of diseases in colonial Africa. The fellows will work closely with the PI and other project
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statistics, including programming in commonly used languages such as R. A valid category B driver’s license, enabling fieldwork in Sweden and abroad. Very good oral and written proficiency in English
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programming, preferably using python or R Experience working with fMRI data Experience working with PET data Familiarity with git and GitHub Familiarity with best practices in reproducibility and open science
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ability experience in R and / or Python. statistical knowledge and application experience handling large datasets Bash / Linux knowledge good experience of English in both spoken and written form self
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microfluidics and lab-on-a-chip technology. Experience in PTM analysis, such as phosphorylation, glycosylation. Experience from programming e.g. in R, Phyton, or equivalent. You should be highly motivated