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Interviews (IDIs), and Key Informant Interviews (KIIs); strong skills in quantitative data collection and analysis, including designing and conducting surveys, and using statistical software such as SPSS, R
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outlook and good communicative skills required to collaborate in a multidisciplinary team demonstrable experience with scientific programming, e.g. in Python, Julia or R proficiency in spoken and written
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regarded as a strong advantage. Familiarity with bioinformatics tools and programming in R or Python is not mandatory but would be considered a valuable asset. Additional Information Benefits Terms
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software such as SPSS, R, etc.; proficiency in spatial analysis tools such as ArcGIS/QGIS or willingness to learn; a demonstrated ability and willingness to spend a good amount of time in the case study
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to study the following references in depth, but you may look into them for a high-level impression of the style of research. H. Fokkema, R. de Heide and T. van Erven. Attribution-based Explanations
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datasets, from i.e. semi-quantitative LC-MS/MS proteomics, therefore proven affinity with R is an asset. You will work here The research is embedded within the chair Toxicology (link internet page Chairgroup
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that you have to work with large datasets, from i.e. semi-quantitative LC-MS/MS proteomics, therefore proven affinity with R is an asset. You will work here The research is embedded within the chair
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. Python, Matlab, and/or R.\ Has interest (and ideally, research and coding experience) in functional MRI methods. Has a strong interest in visual neuroscience and affinity with healthcare applications. Has
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resilient: you are comfortable handling complex data and working in a demanding environment. Experience with statistical software (preferably R. MATLAB, Python) Strong interest in cardiovascular physiology
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programming (e.g., R) and experimental work Proficient communication skills in spoken and written English We are committed to building an inclusive and diverse team, welcoming applications from individuals